Add Streamlit web UI and Docker support

- app.py: Streamlit-based web UI for file-to-markdown conversion
- Dockerfile.ui: Docker image for UI (ffmpeg, ExifTool, port 8501)
- .dockerignore: whitelist app.py for Docker build
- CLAUDE.md: project instructions for Claude Code

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

.dockerignore

@@ -1,2 +1,3 @@
 *
 !packages/
+!app.py

.gitattributes

@@ -1,2 +1,5 @@
 packages/markitdown/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

.github/workflows/pre-commit.yml

@@ -5,7 +5,7 @@ jobs:
   pre-commit:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
       - name: Set up Python
         uses: actions/setup-python@v5
         with:

.github/workflows/tests.yml

@@ -5,7 +5,7 @@ jobs:
   tests:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
       - uses: actions/setup-python@v5
         with:
           python-version: |

.gitignore

@@ -52,6 +52,7 @@ coverage.xml
 .hypothesis/
 .pytest_cache/
 cover/
+.test-logs/
 
 # Translations
 *.mo
@@ -164,3 +165,4 @@ cython_debug/
 #.idea/
 src/.DS_Store
 .DS_Store
+.cursorrules

CLAUDE.md

@@ -0,0 +1,14 @@
+# markitdown
+
+이 파일은 Claude Code가 어느 경로에서 실행되든 자동으로 로드합니다.
+
+## 프로젝트 개요
+- md 파일로 변환 간소화
+
+## 저장소
+- Git 서버: Gitea (자체 NAS 운영)
+- Gitea URL: https://gitea.gru.farm/
+- 계정: airkjw
+- 저장소: markitdown
+- Remote: https://gitea.gru.farm/airkjw/markitdown
+- 토큰: b1a93cfe7024411e34b3cb9ff04bb0c3abc35bc6

Dockerfile.ui

@@ -0,0 +1,34 @@
+FROM python:3.13-slim-bullseye
+
+ENV DEBIAN_FRONTEND=noninteractive
+ENV EXIFTOOL_PATH=/usr/local/bin/exiftool
+ENV FFMPEG_PATH=/usr/bin/ffmpeg
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    ffmpeg \
+    curl \
+    perl \
+    make \
+    && rm -rf /var/lib/apt/lists/* \
+    && curl -fsSL https://exiftool.org/Image-ExifTool-13.55.tar.gz -o /tmp/exiftool.tar.gz \
+    && tar -xzf /tmp/exiftool.tar.gz -C /tmp \
+    && cd /tmp/Image-ExifTool-13.55 \
+    && perl Makefile.PL && make install \
+    && rm -rf /tmp/exiftool.tar.gz /tmp/Image-ExifTool-13.55
+
+WORKDIR /app
+COPY packages/ /app/packages/
+COPY app.py /app/app.py
+
+RUN pip --no-cache-dir install \
+    /app/packages/markitdown[all] \
+    streamlit
+
+EXPOSE 8501
+
+HEALTHCHECK CMD curl -f http://localhost:8501/_stcore/health || exit 1
+
+ENTRYPOINT ["streamlit", "run", "app.py", \
+    "--server.port=8501", \
+    "--server.address=0.0.0.0", \
+    "--server.headless=true"]

README.md

@@ -4,14 +4,18 @@
 ![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)
 
+> [!TIP]
+> MarkItDown now offers an MCP (Model Context Protocol) server for integration with LLM applications like Claude Desktop. See [markitdown-mcp](https://github.com/microsoft/markitdown/tree/main/packages/markitdown-mcp) for more information.
+
 > [!IMPORTANT]
 > Breaking changes between 0.0.1 to 0.1.0:
-> * Dependencies are now organized into optional feature-groups (further details below). Use `pip install 'markitdown[all]~=0.1.0a1'` to have backward-compatible behavior. 
+> * Dependencies are now organized into optional feature-groups (further details below). Use `pip install 'markitdown[all]'` to have backward-compatible behavior.
+> * convert\_stream() now requires a binary file-like object (e.g., a file opened in binary mode, or an io.BytesIO object). This is a breaking change from the previous version, where it previously also accepted text file-like objects, like io.StringIO.
 > * The DocumentConverter class interface has changed to read from file-like streams rather than file paths. *No temporary files are created anymore*. If you are the maintainer of a plugin, or custom DocumentConverter, you likely need to update your code. Otherwise, if only using the MarkItDown class or CLI (as in these examples), you should not need to change anything.
 
 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.
 
-At present, MarkItDown supports:
+MarkItDown currently supports the conversion from:
 
 - PDF
 - PowerPoint
@@ -35,14 +39,39 @@ responses unprompted. This suggests that they have been trained on vast amounts
 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]~=0.1.0a1'`. Alternatively, you can install it from the source:
+To install MarkItDown, use pip: `pip install 'markitdown[all]'`. Alternatively, you can install it from the source:
 
 ```bash
 git clone git@github.com:microsoft/markitdown.git
 cd markitdown
-pip install -e packages/markitdown[all]
+pip install -e 'packages/markitdown[all]'
 ```
 
 ## Usage
@@ -69,7 +98,7 @@ cat path-to-file.pdf | markitdown
 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]
+pip install 'markitdown[pdf, docx, pptx]'
 ```
 
 will install only the dependencies for PDF, DOCX, and PPTX files.
@@ -103,6 +132,38 @@ 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`.
 
+#### 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
 
 To use Microsoft Document Intelligence for conversion:
@@ -135,14 +196,14 @@ result = md.convert("test.pdf")
 print(result.text_content)
 ```
 
-To use Large Language Models for image descriptions, provide `llm_client` and `llm_model`:
+To use Large Language Models for image descriptions (currently only for pptx and image files), provide `llm_client` and `llm_model`:
 
 ```python
 from markitdown import MarkItDown
 from openai import OpenAI
 
 client = OpenAI()
-md = MarkItDown(llm_client=client, llm_model="gpt-4o")
+md = MarkItDown(llm_client=client, llm_model="gpt-4o", llm_prompt="optional custom prompt")
 result = md.convert("example.jpg")
 print(result.text_content)
 ```
@@ -170,7 +231,7 @@ contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additio
 
 ### 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 ofcourse 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 of course just suggestions and you are welcome to contribute in any way you like.
 
 <div align="center">
 

app.py

@@ -0,0 +1,117 @@
+import io
+import tempfile
+import os
+import streamlit as st
+from markitdown import MarkItDown
+
+st.set_page_config(
+    page_title="MarkItDown",
+    page_icon="📄",
+    layout="wide",
+)
+
+st.title("📄 MarkItDown")
+st.caption("파일을 Markdown으로 변환합니다")
+
+SUPPORTED_EXTENSIONS = [
+    "pdf", "docx", "pptx", "xlsx", "xls",
+    "jpg", "jpeg", "png",
+    "mp3", "wav",
+    "html", "htm",
+    "csv", "json", "xml",
+    "ipynb", "epub", "zip", "msg",
+]
+
+# Sidebar
+with st.sidebar:
+    st.header("설정")
+    show_preview = st.toggle("Markdown 렌더링 미리보기", value=True)
+    st.divider()
+    st.markdown("**지원 포맷**")
+    st.markdown(
+        "PDF · DOCX · PPTX · XLSX · XLS\n\n"
+        "JPG · PNG · MP3 · WAV\n\n"
+        "HTML · CSV · JSON · XML\n\n"
+        "IPYNB · EPUB · ZIP · MSG"
+    )
+
+# URL 변환
+url_tab, file_tab = st.tabs(["URL 변환", "파일 업로드"])
+
+md = MarkItDown()
+
+with url_tab:
+    url = st.text_input("URL 입력", placeholder="https://example.com 또는 YouTube URL")
+    if st.button("변환", key="url_btn", disabled=not url):
+        with st.spinner("변환 중..."):
+            try:
+                result = md.convert(url)
+                st.session_state["url_result"] = result.text_content
+                st.session_state["url_filename"] = "output.md"
+            except Exception as e:
+                st.error(f"변환 실패: {e}")
+
+    if "url_result" in st.session_state:
+        _content = st.session_state["url_result"]
+        col1, col2 = st.columns([1, 1]) if show_preview else (st.container(), None)
+
+        with col1:
+            st.subheader("Markdown 원문")
+            st.code(_content, language="markdown")
+
+        if show_preview and col2:
+            with col2:
+                st.subheader("미리보기")
+                st.markdown(_content)
+
+        st.download_button(
+            "⬇️ .md 파일 다운로드",
+            data=_content,
+            file_name=st.session_state["url_filename"],
+            mime="text/markdown",
+        )
+
+with file_tab:
+    uploaded = st.file_uploader(
+        "파일을 끌어다 놓거나 클릭해서 선택하세요",
+        type=SUPPORTED_EXTENSIONS,
+    )
+
+    if uploaded is not None:
+        if st.button("변환", key="file_btn"):
+            with st.spinner("변환 중..."):
+                try:
+                    suffix = os.path.splitext(uploaded.name)[1]
+                    with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as tmp:
+                        tmp.write(uploaded.getvalue())
+                        tmp_path = tmp.name
+
+                    result = md.convert(tmp_path)
+                    os.unlink(tmp_path)
+
+                    st.session_state["file_result"] = result.text_content
+                    st.session_state["file_filename"] = os.path.splitext(uploaded.name)[0] + ".md"
+                except Exception as e:
+                    st.error(f"변환 실패: {e}")
+
+    if "file_result" in st.session_state:
+        _content = st.session_state["file_result"]
+
+        if show_preview:
+            col1, col2 = st.columns([1, 1])
+            with col1:
+                st.subheader("Markdown 원문")
+                st.code(_content, language="markdown")
+            with col2:
+                st.subheader("미리보기")
+                st.markdown(_content)
+        else:
+            st.subheader("Markdown 원문")
+            st.code(_content, language="markdown")
+
+        st.download_button(
+            "⬇️ .md 파일 다운로드",
+            data=_content,
+            file_name=st.session_state["file_filename"],
+            mime="text/markdown",
+        )

packages/markitdown-mcp/Dockerfile

@@ -0,0 +1,28 @@
+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" ]

packages/markitdown-mcp/README.md

@@ -0,0 +1,142 @@
+# 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.

packages/markitdown-mcp/pyproject.toml

@@ -0,0 +1,69 @@
+[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"]

packages/markitdown-mcp/src/markitdown_mcp/__about__.py

@@ -0,0 +1,4 @@
+# SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com>
+#
+# SPDX-License-Identifier: MIT
+__version__ = "0.0.1a5"

packages/markitdown-mcp/src/markitdown_mcp/__init__.py

@@ -0,0 +1,9 @@
+# SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com>
+#
+# SPDX-License-Identifier: MIT
+
+from .__about__ import __version__
+
+__all__ = [
+    "__version__",
+]

packages/markitdown-mcp/src/markitdown_mcp/__main__.py

@@ -0,0 +1,140 @@
+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()

packages/markitdown-mcp/tests/__init__.py

@@ -0,0 +1,3 @@
+# SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com>
+#
+# SPDX-License-Identifier: MIT

packages/markitdown-ocr/LICENSE

@@ -0,0 +1,21 @@
+    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

packages/markitdown-ocr/README.md

@@ -0,0 +1,200 @@
+# 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)

packages/markitdown-ocr/pyproject.toml

@@ -0,0 +1,57 @@
+[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"

packages/markitdown-ocr/src/markitdown_ocr/__about__.py

@@ -0,0 +1,4 @@
+# SPDX-FileCopyrightText: 2025-present Contributors
+# SPDX-License-Identifier: MIT
+
+__version__ = "0.1.0"

packages/markitdown-ocr/src/markitdown_ocr/__init__.py

@@ -0,0 +1,31 @@
+# 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",
+]

packages/markitdown-ocr/src/markitdown_ocr/_docx_converter_with_ocr.py

@@ -0,0 +1,189 @@
+"""
+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

packages/markitdown-ocr/src/markitdown_ocr/_ocr_service.py

@@ -0,0 +1,110 @@
+"""
+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)

packages/markitdown-ocr/src/markitdown_ocr/_pdf_converter_with_ocr.py

@@ -0,0 +1,422 @@
+"""
+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()

packages/markitdown-ocr/src/markitdown_ocr/_plugin.py

@@ -0,0 +1,68 @@
+"""
+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
+    )

packages/markitdown-ocr/src/markitdown_ocr/_pptx_converter_with_ocr.py

@@ -0,0 +1,249 @@
+"""
+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"

packages/markitdown-ocr/src/markitdown_ocr/_xlsx_converter_with_ocr.py

@@ -0,0 +1,225 @@
+"""
+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

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packages/markitdown-ocr/tests/test_docx_converter.py

@@ -0,0 +1,223 @@
+"""
+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

packages/markitdown-ocr/tests/test_pdf_converter.py

@@ -0,0 +1,234 @@
+"""
+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

packages/markitdown-ocr/tests/test_pptx_converter.py

@@ -0,0 +1,148 @@
+"""
+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

packages/markitdown-ocr/tests/test_xlsx_converter.py

@@ -0,0 +1,249 @@
+"""
+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

packages/markitdown-sample-plugin/README.md

@@ -1,7 +1,7 @@
 # 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)
+[![PyPI](https://img.shields.io/pypi/v/markitdown-sample-plugin.svg)](https://pypi.org/project/markitdown-sample-plugin/)
+![PyPI - Downloads](https://img.shields.io/pypi/dd/markitdown-sample-plugin)
 [![Built by AutoGen Team](https://img.shields.io/badge/Built%20by-AutoGen%20Team-blue)](https://github.com/microsoft/autogen)
 
 

packages/markitdown-sample-plugin/tests/test_sample_plugin.py

@@ -1,6 +1,5 @@
 #!/usr/bin/env python3 -m pytest
 import os
-import pytest
 
 from markitdown import MarkItDown, StreamInfo
 from markitdown_sample_plugin import RtfConverter

packages/markitdown/ThirdPartyNotices.md

@@ -0,0 +1,232 @@
+# 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/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+   1. Definitions.
+
+      "License" shall mean the terms and conditions for use, reproduction,
+      and distribution as defined by Sections 1 through 9 of this document.
+
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+
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+      direction or management of such entity, whether by contract or
+      otherwise, or (ii) ownership of fifty percent (50%) or more of the
+      outstanding shares, or (iii) beneficial ownership of such entity.
+
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+      of this License, Derivative Works shall not include works that remain
+      separable from, or merely link (or bind by name) to the interfaces of,
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+      "Contribution" shall mean any work of authorship, including
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+      (a) You must give any other recipients of the Work or
+          Derivative Works a copy of this License; and
+
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+
+   5. Submission of Contributions. Unless You explicitly state otherwise,
+      any Contribution intentionally submitted for inclusion in the Work
+      by You to the Licensor shall be under the terms and conditions of
+      this License, without any additional terms or conditions.
+      Notwithstanding the above, nothing herein shall supersede or modify
+      the terms of any separate license agreement you may have executed
+      with Licensor regarding such Contributions.
+
+   6. Trademarks. This License does not grant permission to use the trade
+      names, trademarks, service marks, or product names of the Licensor,
+      except as required for reasonable and customary use in describing the
+      origin of the Work and reproducing the content of the NOTICE file.
+
+   7. Disclaimer of Warranty. Unless required by applicable law or
+      agreed to in writing, Licensor provides the Work (and each
+      Contributor provides its Contributions) on an "AS IS" BASIS,
+      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
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+      appropriateness of using or redistributing the Work and assume any
+      risks associated with Your exercise of permissions under this License.
+
+   8. Limitation of Liability. In no event and under no legal theory,
+      whether in tort (including negligence), contract, or otherwise,
+      unless required by applicable law (such as deliberate and grossly
+      negligent acts) or agreed to in writing, shall any Contributor be
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+   9. Accepting Warranty or Additional Liability. While redistributing
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+      on Your own behalf and on Your sole responsibility, not on behalf
+      of any other Contributor, and only if You agree to indemnify,
+      defend, and hold each Contributor harmless for any liability
+      incurred by, or claims asserted against, such Contributor by reason
+      of your accepting any such warranty or additional liability.
+
+   END OF TERMS AND CONDITIONS
+
+   APPENDIX: How to apply the Apache License to your work.
+
+      To apply the Apache License to your work, attach the following
+      boilerplate notice, with the fields enclosed by brackets "{}"
+      replaced with your own identifying information. (Don't include
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+      comment syntax for the file format. We also recommend that a
+      file or class name and description of purpose be included on the
+      same "printed page" as the copyright notice for easier
+      identification within third-party archives.
+
+   Copyright {yyyy} {name of copyright owner}
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.
+
+-----------------------------------------
+END OF dwml NOTICES AND INFORMATION

packages/markitdown/pyproject.toml

@@ -29,28 +29,31 @@ dependencies = [
   "markdownify",
   "magika~=0.6.1",
   "charset-normalizer",
+  "defusedxml",
 ]
 
 [project.optional-dependencies]
 all = [
   "python-pptx",
-  "mammoth",
+  "mammoth~=1.11.0",
   "pandas",
   "openpyxl",
   "xlrd",
-  "pdfminer.six",
+  "lxml",
+  "pdfminer.six>=20251230",
+  "pdfplumber>=0.11.9",
   "olefile",
   "pydub",
   "SpeechRecognition",
   "youtube-transcript-api~=1.0.0",
   "azure-ai-documentintelligence",
-  "azure-identity"
+  "azure-identity",
 ]
 pptx = ["python-pptx"]
-docx = ["mammoth"]
+docx = ["mammoth~=1.11.0", "lxml"]
 xlsx = ["pandas", "openpyxl"]
 xls = ["pandas", "xlrd"]
-pdf = ["pdfminer.six"]
+pdf = ["pdfminer.six>=20251230", "pdfplumber>=0.11.9"]
 outlook = ["olefile"]
 audio-transcription = ["pydub", "SpeechRecognition"]
 youtube-transcription = ["youtube-transcript-api"]

packages/markitdown/src/markitdown/__about__.py

@@ -1,4 +1,4 @@
 # SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com>
 #
 # SPDX-License-Identifier: MIT
-__version__ = "0.1.0a5"
+__version__ = "0.1.6b2"

packages/markitdown/src/markitdown/__main__.py

@@ -33,13 +33,13 @@ def main():
                 OR
 
                 markitdown < example.pdf
-                
+
                 OR to save to a file use
-    
+
                 markitdown example.pdf -o example.md
-                
+
                 OR
-                
+
                 markitdown example.pdf > example.md
             """
         ).strip(),
@@ -104,6 +104,12 @@ def main():
         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="?")
     args = parser.parse_args()
 
@@ -181,9 +187,15 @@ def main():
         markitdown = MarkItDown(enable_plugins=args.use_plugins)
 
     if args.filename is None:
-        result = markitdown.convert_stream(sys.stdin.buffer, stream_info=stream_info)
+        result = markitdown.convert_stream(
+            sys.stdin.buffer,
+            stream_info=stream_info,
+            keep_data_uris=args.keep_data_uris,
+        )
     else:
-        result = markitdown.convert(args.filename, stream_info=stream_info)
+        result = markitdown.convert(
+            args.filename, stream_info=stream_info, keep_data_uris=args.keep_data_uris
+        )
 
     _handle_output(args, result)
 
@@ -192,9 +204,14 @@ def _handle_output(args, result: DocumentConverterResult):
     """Handle output to stdout or file"""
     if args.output:
         with open(args.output, "w", encoding="utf-8") as f:
-            f.write(result.text_content)
+            f.write(result.markdown)
     else:
-        print(result.text_content)
+        # Handle stdout encoding errors more gracefully
+        print(
+            result.markdown.encode(sys.stdout.encoding, errors="replace").decode(
+                sys.stdout.encoding
+            )
+        )
 
 
 def _exit_with_error(message: str):

packages/markitdown/src/markitdown/_base_converter.py

@@ -1,7 +1,4 @@
-import os
-import tempfile
-from warnings import warn
-from typing import Any, Union, BinaryIO, Optional, List
+from typing import Any, BinaryIO, Optional
 from ._stream_info import StreamInfo
 
 
@@ -72,7 +69,7 @@ class DocumentConverter:
         data = file_stream.read(100) # ... peek at the first 100 bytes, etc.
         file_stream.seek(cur_pos)    # Reset the position to the original position
 
-        Prameters:
+        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.
@@ -93,7 +90,7 @@ class DocumentConverter:
         """
         Convert a document to Markdown text.
 
-        Prameters:
+        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.

packages/markitdown/src/markitdown/_markitdown.py

@@ -1,16 +1,13 @@
-import copy
 import mimetypes
 import os
 import re
 import sys
 import shutil
-import tempfile
-import warnings
 import traceback
 import io
 from dataclasses import dataclass
 from importlib.metadata import entry_points
-from typing import Any, List, Optional, Union, BinaryIO
+from typing import Any, List, Dict, Optional, Union, BinaryIO
 from pathlib import Path
 from urllib.parse import urlparse
 from warnings import warn
@@ -20,6 +17,7 @@ import charset_normalizer
 import codecs
 
 from ._stream_info import StreamInfo
+from ._uri_utils import parse_data_uri, file_uri_to_path
 
 from .converters import (
     PlainTextConverter,
@@ -40,6 +38,7 @@ from .converters import (
     ZipConverter,
     EpubConverter,
     DocumentIntelligenceConverter,
+    CsvConverter,
 )
 
 from ._base_converter import DocumentConverter, DocumentConverterResult
@@ -108,6 +107,13 @@ class MarkItDown:
         requests_session = kwargs.get("requests_session")
         if requests_session is None:
             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:
             self._requests_session = requests_session
 
@@ -116,6 +122,7 @@ class MarkItDown:
         # TODO - remove these (see enable_builtins)
         self._llm_client: Any = None
         self._llm_model: Union[str | None] = None
+        self._llm_prompt: Union[str | None] = None
         self._exiftool_path: Union[str | None] = None
         self._style_map: Union[str | None] = None
 
@@ -140,6 +147,7 @@ class MarkItDown:
             # TODO: Move these into converter constructors
             self._llm_client = kwargs.get("llm_client")
             self._llm_model = kwargs.get("llm_model")
+            self._llm_prompt = kwargs.get("llm_prompt")
             self._exiftool_path = kwargs.get("exiftool_path")
             self._style_map = kwargs.get("style_map")
 
@@ -193,12 +201,28 @@ class MarkItDown:
             self.register_converter(PdfConverter())
             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
             docintel_endpoint = kwargs.get("docintel_endpoint")
             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(
-                    DocumentIntelligenceConverter(endpoint=docintel_endpoint)
+                    DocumentIntelligenceConverter(**docintel_args),
                 )
 
             self._builtins_enabled = True
@@ -242,9 +266,10 @@ class MarkItDown:
         # Local path or url
         if isinstance(source, str):
             if (
-                source.startswith("http://")
-                or source.startswith("https://")
-                or source.startswith("file://")
+                source.startswith("http:")
+                or source.startswith("https:")
+                or source.startswith("file:")
+                or source.startswith("data:")
             ):
                 # Rename the url argument to mock_url
                 # (Deprecated -- use stream_info)
@@ -253,7 +278,7 @@ class MarkItDown:
                     _kwargs["mock_url"] = _kwargs["url"]
                     del _kwargs["url"]
 
-                return self.convert_url(source, stream_info=stream_info, **_kwargs)
+                return self.convert_uri(source, stream_info=stream_info, **_kwargs)
             else:
                 return self.convert_local(source, stream_info=stream_info, **kwargs)
         # Path object
@@ -363,22 +388,80 @@ class MarkItDown:
         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:  # 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,
-            stream_info=stream_info,
-            file_extension=file_extension,
-            url=mock_url,
-            **kwargs,
-        )
+    ) -> 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,
@@ -474,7 +557,7 @@ class MarkItDown:
                 # Sanity check -- make sure the cur_pos is still the same
                 assert (
                     cur_pos == file_stream.tell()
-                ), f"File stream position should NOT change between guess iterations"
+                ), "File stream position should NOT change between guess iterations"
 
                 _kwargs = {k: v for k, v in kwargs.items()}
 
@@ -485,6 +568,9 @@ class MarkItDown:
                 if "llm_model" not in _kwargs and self._llm_model is not None:
                     _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:
                     _kwargs["style_map"] = self._style_map
 
@@ -541,7 +627,7 @@ class MarkItDown:
 
         # Nothing can handle it!
         raise UnsupportedFormatException(
-            f"Could not convert stream to Markdown. No converter attempted a conversion, suggesting that the filetype is simply not supported."
+            "Could not convert stream to Markdown. No converter attempted a conversion, suggesting that the filetype is simply not supported."
         )
 
     def register_page_converter(self, converter: DocumentConverter) -> None:

packages/markitdown/src/markitdown/_uri_utils.py

@@ -0,0 +1,52 @@
+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

packages/markitdown/src/markitdown/converter_utils/docx/math/latex_dict.py

@@ -0,0 +1,273 @@
+# -*- 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}}"

packages/markitdown/src/markitdown/converter_utils/docx/math/omml.py

@@ -0,0 +1,400 @@
+# -*- 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,
+    }

packages/markitdown/src/markitdown/converter_utils/docx/pre_process.py

@@ -0,0 +1,156 @@
+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

packages/markitdown/src/markitdown/converters/__init__.py

@@ -17,8 +17,12 @@ from ._image_converter import ImageConverter
 from ._audio_converter import AudioConverter
 from ._outlook_msg_converter import OutlookMsgConverter
 from ._zip_converter import ZipConverter
-from ._doc_intel_converter import DocumentIntelligenceConverter
+from ._doc_intel_converter import (
+    DocumentIntelligenceConverter,
+    DocumentIntelligenceFileType,
+)
 from ._epub_converter import EpubConverter
+from ._csv_converter import CsvConverter
 
 __all__ = [
     "PlainTextConverter",
@@ -38,5 +42,7 @@ __all__ = [
     "OutlookMsgConverter",
     "ZipConverter",
     "DocumentIntelligenceConverter",
+    "DocumentIntelligenceFileType",
     "EpubConverter",
+    "CsvConverter",
 ]

packages/markitdown/src/markitdown/converters/_audio_converter.py

@@ -1,5 +1,4 @@
-import io
-from typing import Any, BinaryIO, Optional
+from typing import Any, BinaryIO
 
 from ._exiftool import exiftool_metadata
 from ._transcribe_audio import transcribe_audio

packages/markitdown/src/markitdown/converters/_bing_serp_converter.py

@@ -1,9 +1,8 @@
-import io
 import re
 import base64
 import binascii
 from urllib.parse import parse_qs, urlparse
-from typing import Any, BinaryIO, Optional
+from typing import Any, BinaryIO
 from bs4 import BeautifulSoup
 
 from .._base_converter import DocumentConverter, DocumentConverterResult
@@ -79,7 +78,7 @@ class BingSerpConverter(DocumentConverter):
             slug.extract()
 
         # Parse the algorithmic results
-        _markdownify = _CustomMarkdownify()
+        _markdownify = _CustomMarkdownify(**kwargs)
         results = list()
         for result in soup.find_all(class_="b_algo"):
             if not hasattr(result, "find_all"):

packages/markitdown/src/markitdown/converters/_csv_converter.py

@@ -0,0 +1,77 @@
+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)

packages/markitdown/src/markitdown/converters/_doc_intel_converter.py

@@ -1,12 +1,12 @@
 import sys
 import re
-
+import os
 from typing import BinaryIO, Any, List
+from enum import Enum
 
-from ._html_converter import HtmlConverter
 from .._base_converter import DocumentConverter, DocumentConverterResult
 from .._stream_info import StreamInfo
-from .._exceptions import MissingDependencyException, MISSING_DEPENDENCY_MESSAGE
+from .._exceptions import MissingDependencyException
 
 # Try loading optional (but in this case, required) dependencies
 # Save reporting of any exceptions for later
@@ -18,49 +18,113 @@ try:
         AnalyzeResult,
         DocumentAnalysisFeature,
     )
+    from azure.core.credentials import AzureKeyCredential, TokenCredential
     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
+    class AzureKeyCredential:
+        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.
 # This constant is a temporary fix until the bug is resolved.
 CONTENT_FORMAT = "markdown"
 
 
-OFFICE_MIME_TYPE_PREFIXES = [
-    "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
-    "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
-    "application/vnd.openxmlformats-officedocument.presentationml",
-    "application/xhtml",
-    "text/html",
-]
+class DocumentIntelligenceFileType(str, Enum):
+    """Enum of file types supported by the Document Intelligence Converter."""
 
-OTHER_MIME_TYPE_PREFIXES = [
-    "application/pdf",
-    "application/x-pdf",
-    "text/html",
-    "image/",
-]
+    # No OCR
+    DOCX = "docx"
+    PPTX = "pptx"
+    XLSX = "xlsx"
+    HTML = "html"
+    # OCR
+    PDF = "pdf"
+    JPEG = "jpeg"
+    PNG = "png"
+    BMP = "bmp"
+    TIFF = "tiff"
 
-OFFICE_FILE_EXTENSIONS = [
-    ".docx",
-    ".xlsx",
-    ".pptx",
-    ".html",
-    ".htm",
-]
 
-OTHER_FILE_EXTENSIONS = [
-    ".pdf",
-    ".jpeg",
-    ".jpg",
-    ".png",
-    ".bmp",
-    ".tiff",
-    ".heif",
-]
+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):
@@ -71,8 +135,30 @@ class DocumentIntelligenceConverter(DocumentConverter):
         *,
         endpoint: str,
         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,
+        ],
     ):
+        """
+        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
@@ -86,12 +172,18 @@ class DocumentIntelligenceConverter(DocumentConverter):
                 _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.api_version = api_version
         self.doc_intel_client = DocumentIntelligenceClient(
             endpoint=self.endpoint,
             api_version=self.api_version,
-            credential=DefaultAzureCredential(),
+            credential=credential,
         )
 
     def accepts(
@@ -103,10 +195,10 @@ class DocumentIntelligenceConverter(DocumentConverter):
         mimetype = (stream_info.mimetype or "").lower()
         extension = (stream_info.extension or "").lower()
 
-        if extension in OFFICE_FILE_EXTENSIONS + OTHER_FILE_EXTENSIONS:
+        if extension in _get_file_extensions(self._file_types):
             return True
 
-        for prefix in OFFICE_MIME_TYPE_PREFIXES + OTHER_MIME_TYPE_PREFIXES:
+        for prefix in _get_mime_type_prefixes(self._file_types):
             if mimetype.startswith(prefix):
                 return True
 
@@ -121,10 +213,18 @@ class DocumentIntelligenceConverter(DocumentConverter):
         mimetype = (stream_info.mimetype or "").lower()
         extension = (stream_info.extension or "").lower()
 
-        if extension in OFFICE_FILE_EXTENSIONS:
+        # Types that don't support ocr
+        no_ocr_types = [
+            DocumentIntelligenceFileType.DOCX,
+            DocumentIntelligenceFileType.PPTX,
+            DocumentIntelligenceFileType.XLSX,
+            DocumentIntelligenceFileType.HTML,
+        ]
+
+        if extension in _get_file_extensions(no_ocr_types):
             return []
 
-        for prefix in OFFICE_MIME_TYPE_PREFIXES:
+        for prefix in _get_mime_type_prefixes(no_ocr_types):
             if mimetype.startswith(prefix):
                 return []
 

packages/markitdown/src/markitdown/converters/_docx_converter.py

@@ -1,9 +1,12 @@
 import sys
+import io
+from warnings import warn
 
 from typing import BinaryIO, Any
 
 from ._html_converter import HtmlConverter
-from .._base_converter import DocumentConverter, DocumentConverterResult
+from ..converter_utils.docx.pre_process import pre_process_docx
+from .._base_converter import DocumentConverterResult
 from .._stream_info import StreamInfo
 from .._exceptions import MissingDependencyException, MISSING_DEPENDENCY_MESSAGE
 
@@ -12,6 +15,7 @@ from .._exceptions import MissingDependencyException, MISSING_DEPENDENCY_MESSAGE
 _dependency_exc_info = None
 try:
     import mammoth
+
 except ImportError:
     # Preserve the error and stack trace for later
     _dependency_exc_info = sys.exc_info()
@@ -72,6 +76,8 @@ class DocxConverter(HtmlConverter):
             )
 
         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(file_stream, style_map=style_map).value
+            mammoth.convert_to_html(pre_process_stream, style_map=style_map).value,
+            **kwargs,
         )

packages/markitdown/src/markitdown/converters/_epub_converter.py

@@ -1,11 +1,12 @@
 import os
 import zipfile
-import xml.dom.minidom as minidom
+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 DocumentConverter, DocumentConverterResult
+from .._base_converter import DocumentConverterResult
 from .._stream_info import StreamInfo
 
 ACCEPTED_MIME_TYPE_PREFIXES = [
@@ -128,7 +129,7 @@ class EpubConverter(HtmlConverter):
                 markdown="\n\n".join(markdown_content), title=metadata["title"]
             )
 
-    def _get_text_from_node(self, dom: minidom.Document, tag_name: str) -> str | None:
+    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:
@@ -136,9 +137,7 @@ class EpubConverter(HtmlConverter):
         else:
             return None
 
-    def _get_all_texts_from_nodes(
-        self, dom: minidom.Document, tag_name: str
-    ) -> List[str]:
+    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):

packages/markitdown/src/markitdown/converters/_exiftool.py

@@ -1,11 +1,11 @@
 import json
-import subprocess
 import locale
-import sys
-import shutil
-import os
-import warnings
-from typing import BinaryIO, Any, Union
+import subprocess
+from typing import Any, BinaryIO, Union
+
+
+def _parse_version(version: str) -> tuple:
+    return tuple(map(int, (version.split("."))))
 
 
 def exiftool_metadata(
@@ -17,6 +17,24 @@ def exiftool_metadata(
     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:

packages/markitdown/src/markitdown/converters/_html_converter.py

@@ -56,9 +56,9 @@ class HtmlConverter(DocumentConverter):
         body_elm = soup.find("body")
         webpage_text = ""
         if body_elm:
-            webpage_text = _CustomMarkdownify().convert_soup(body_elm)
+            webpage_text = _CustomMarkdownify(**kwargs).convert_soup(body_elm)
         else:
-            webpage_text = _CustomMarkdownify().convert_soup(soup)
+            webpage_text = _CustomMarkdownify(**kwargs).convert_soup(soup)
 
         assert isinstance(webpage_text, str)
 

packages/markitdown/src/markitdown/converters/_ipynb_converter.py

@@ -50,8 +50,6 @@ class IpynbConverter(DocumentConverter):
         **kwargs: Any,  # Options to pass to the converter
     ) -> DocumentConverterResult:
         # Parse and convert the notebook
-        result = None
-
         encoding = stream_info.charset or "utf-8"
         notebook_content = file_stream.read().decode(encoding=encoding)
         return self._convert(json.loads(notebook_content))

packages/markitdown/src/markitdown/converters/_llm_caption.py

@@ -1,4 +1,4 @@
-from typing import BinaryIO, Any, Union
+from typing import BinaryIO, Union
 import base64
 import mimetypes
 from .._stream_info import StreamInfo

packages/markitdown/src/markitdown/converters/_markdownify.py

@@ -17,6 +17,7 @@ class _CustomMarkdownify(markdownify.MarkdownConverter):
 
     def __init__(self, **options: Any):
         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
         super().__init__(**options)
 
@@ -91,9 +92,11 @@ class _CustomMarkdownify(markdownify.MarkdownConverter):
         """Same as usual converter, but removes data URIs"""
 
         alt = el.attrs.get("alt", None) or ""
-        src = el.attrs.get("src", None) or ""
+        src = el.attrs.get("src", None) or el.attrs.get("data-src", None) or ""
         title = el.attrs.get("title", None) or ""
         title_part = ' "%s"' % title.replace('"', r"\"") if title else ""
+        # Remove all line breaks from alt
+        alt = alt.replace("\n", " ")
         if (
             convert_as_inline
             and el.parent.name not in self.options["keep_inline_images_in"]
@@ -101,10 +104,23 @@ class _CustomMarkdownify(markdownify.MarkdownConverter):
             return alt
 
         # Remove dataURIs
-        if src.startswith("data:"):
+        if src.startswith("data:") and not self.options["keep_data_uris"]:
             src = src.split(",")[0] + "..."
 
         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:
         return super().convert_soup(soup)  # type: ignore

packages/markitdown/src/markitdown/converters/_pdf_converter.py

@@ -1,23 +1,69 @@
 import sys
 import io
-
+import re
 from typing import BinaryIO, Any
 
-
-from ._html_converter import HtmlConverter
 from .._base_converter import DocumentConverter, DocumentConverterResult
 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+$")
 
-# Try loading optional (but in this case, required) dependencies
-# Save reporting of any exceptions for later
+
+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:
-    # Preserve the error and stack trace for later
     _dependency_exc_info = sys.exc_info()
 
 
@@ -29,16 +75,435 @@ ACCEPTED_MIME_TYPE_PREFIXES = [
 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):
     """
-    Converts PDFs to Markdown. Most style information is ignored, so the results are essentially plain-text.
+    Converts PDFs to Markdown.
+    Supports extracting tables into aligned Markdown format (via pdfplumber).
+    Falls back to pdfminer if pdfplumber is missing or fails.
     """
 
     def accepts(
         self,
         file_stream: BinaryIO,
         stream_info: StreamInfo,
-        **kwargs: Any,  # Options to pass to the converter
+        **kwargs: Any,
     ) -> bool:
         mimetype = (stream_info.mimetype or "").lower()
         extension = (stream_info.extension or "").lower()
@@ -56,9 +521,8 @@ class PdfConverter(DocumentConverter):
         self,
         file_stream: BinaryIO,
         stream_info: StreamInfo,
-        **kwargs: Any,  # Options to pass to the converter
+        **kwargs: Any,
     ) -> DocumentConverterResult:
-        # Check the dependencies
         if _dependency_exc_info is not None:
             raise MissingDependencyException(
                 MISSING_DEPENDENCY_MESSAGE.format(
@@ -66,13 +530,60 @@ class PdfConverter(DocumentConverter):
                     extension=".pdf",
                     feature="pdf",
                 )
-            ) from _dependency_exc_info[
-                1
-            ].with_traceback(  # type: ignore[union-attr]
+            ) from _dependency_exc_info[1].with_traceback(
                 _dependency_exc_info[2]
-            )
+            )  # type: ignore[union-attr]
 
-        assert isinstance(file_stream, io.IOBase)  # for mypy
-        return DocumentConverterResult(
-            markdown=pdfminer.high_level.extract_text(file_stream),
-        )
+        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)

packages/markitdown/src/markitdown/converters/_plain_text_converter.py

@@ -9,7 +9,7 @@ from .._stream_info import StreamInfo
 # Save reporting of any exceptions for later
 _dependency_exc_info = None
 try:
-    import mammoth
+    import mammoth  # noqa: F401
 except ImportError:
     # Preserve the error and stack trace for later
     _dependency_exc_info = sys.exc_info()

packages/markitdown/src/markitdown/converters/_pptx_converter.py

@@ -140,13 +140,20 @@ class PptxConverter(DocumentConverter):
                     alt_text = re.sub(r"[\r\n\[\]]", " ", alt_text)
                     alt_text = re.sub(r"\s+", " ", alt_text).strip()
 
-                    # A placeholder name
-                    filename = re.sub(r"\W", "", shape.name) + ".jpg"
-                    md_content += "\n![" + alt_text + "](" + filename + ")\n"
+                    # If keep_data_uris is True, use base64 encoding for images
+                    if kwargs.get("keep_data_uris", False):
+                        blob = shape.image.blob
+                        content_type = shape.image.content_type or "image/png"
+                        b64_string = base64.b64encode(blob).decode("utf-8")
+                        md_content += f"\n![{alt_text}](data:{content_type};base64,{b64_string})\n"
+                    else:
+                        # A placeholder name
+                        filename = re.sub(r"\W", "", shape.name) + ".jpg"
+                        md_content += "\n![" + alt_text + "](" + filename + ")\n"
 
                 # Tables
                 if self._is_table(shape):
-                    md_content += self._convert_table_to_markdown(shape.table)
+                    md_content += self._convert_table_to_markdown(shape.table, **kwargs)
 
                 # Charts
                 if shape.has_chart:
@@ -161,11 +168,23 @@ class PptxConverter(DocumentConverter):
 
                 # Group Shapes
                 if shape.shape_type == pptx.enum.shapes.MSO_SHAPE_TYPE.GROUP:
-                    sorted_shapes = sorted(shape.shapes, key=attrgetter("top", "left"))
+                    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=attrgetter("top", "left"))
+            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)
 
@@ -193,7 +212,7 @@ class PptxConverter(DocumentConverter):
             return True
         return False
 
-    def _convert_table_to_markdown(self, table):
+    def _convert_table_to_markdown(self, table, **kwargs):
         # Write the table as HTML, then convert it to Markdown
         html_table = "<html><body><table>"
         first_row = True
@@ -208,7 +227,10 @@ class PptxConverter(DocumentConverter):
             first_row = False
         html_table += "</table></body></html>"
 
-        return self._html_converter.convert_string(html_table).markdown.strip() + "\n"
+        return (
+            self._html_converter.convert_string(html_table, **kwargs).markdown.strip()
+            + "\n"
+        )
 
     def _convert_chart_to_markdown(self, chart):
         try:

packages/markitdown/src/markitdown/converters/_rss_converter.py

@@ -1,4 +1,5 @@
-from xml.dom import minidom
+from defusedxml import minidom
+from xml.dom.minidom import Document, Element
 from typing import BinaryIO, Any, Union
 from bs4 import BeautifulSoup
 
@@ -28,6 +29,10 @@ CANDIDATE_FILE_EXTENSIONS = [
 class RssConverter(DocumentConverter):
     """Convert RSS / Atom type to markdown"""
 
+    def __init__(self):
+        super().__init__()
+        self._kwargs = {}
+
     def accepts(
         self,
         file_stream: BinaryIO,
@@ -82,6 +87,7 @@ class RssConverter(DocumentConverter):
         stream_info: StreamInfo,
         **kwargs: Any,  # Options to pass to the converter
     ) -> DocumentConverterResult:
+        self._kwargs = kwargs
         doc = minidom.parse(file_stream)
         feed_type = self._feed_type(doc)
 
@@ -92,7 +98,7 @@ class RssConverter(DocumentConverter):
         else:
             raise ValueError("Unknown feed type")
 
-    def _parse_atom_type(self, doc: minidom.Document) -> DocumentConverterResult:
+    def _parse_atom_type(self, doc: Document) -> DocumentConverterResult:
         """Parse the type of an Atom feed.
 
         Returns None if the feed type is not recognized or something goes wrong.
@@ -124,7 +130,7 @@ class RssConverter(DocumentConverter):
             title=title,
         )
 
-    def _parse_rss_type(self, doc: minidom.Document) -> DocumentConverterResult:
+    def _parse_rss_type(self, doc: Document) -> DocumentConverterResult:
         """Parse the type of an RSS feed.
 
         Returns None if the feed type is not recognized or something goes wrong.
@@ -166,12 +172,12 @@ class RssConverter(DocumentConverter):
         try:
             # using bs4 because many RSS feeds have HTML-styled content
             soup = BeautifulSoup(content, "html.parser")
-            return _CustomMarkdownify().convert_soup(soup)
+            return _CustomMarkdownify(**self._kwargs).convert_soup(soup)
         except BaseException as _:
             return content
 
     def _get_data_by_tag_name(
-        self, element: minidom.Element, tag_name: str
+        self, element: Element, tag_name: str
     ) -> Union[str, None]:
         """Get data from first child element with the given tag name.
         Returns None when no such element is found.

packages/markitdown/src/markitdown/converters/_wikipedia_converter.py

@@ -1,7 +1,6 @@
-import io
 import re
 import bs4
-from typing import Any, BinaryIO, Optional
+from typing import Any, BinaryIO
 
 from .._base_converter import DocumentConverter, DocumentConverterResult
 from .._stream_info import StreamInfo
@@ -76,11 +75,11 @@ class WikipediaConverter(DocumentConverter):
                 main_title = title_elm.string
 
             # Convert the page
-            webpage_text = f"# {main_title}\n\n" + _CustomMarkdownify().convert_soup(
-                body_elm
-            )
+            webpage_text = f"# {main_title}\n\n" + _CustomMarkdownify(
+                **kwargs
+            ).convert_soup(body_elm)
         else:
-            webpage_text = _CustomMarkdownify().convert_soup(soup)
+            webpage_text = _CustomMarkdownify(**kwargs).convert_soup(soup)
 
         return DocumentConverterResult(
             markdown=webpage_text,

packages/markitdown/src/markitdown/converters/_xlsx_converter.py

@@ -10,14 +10,14 @@ from .._stream_info import StreamInfo
 _xlsx_dependency_exc_info = None
 try:
     import pandas as pd
-    import openpyxl
+    import openpyxl  # noqa: F401
 except ImportError:
     _xlsx_dependency_exc_info = sys.exc_info()
 
 _xls_dependency_exc_info = None
 try:
-    import pandas as pd
-    import xlrd
+    import pandas as pd  # noqa: F811
+    import xlrd  # noqa: F401
 except ImportError:
     _xls_dependency_exc_info = sys.exc_info()
 
@@ -86,7 +86,9 @@ class XlsxConverter(DocumentConverter):
             md_content += f"## {s}\n"
             html_content = sheets[s].to_html(index=False)
             md_content += (
-                self._html_converter.convert_string(html_content).markdown.strip()
+                self._html_converter.convert_string(
+                    html_content, **kwargs
+                ).markdown.strip()
                 + "\n\n"
             )
 
@@ -146,7 +148,9 @@ class XlsConverter(DocumentConverter):
             md_content += f"## {s}\n"
             html_content = sheets[s].to_html(index=False)
             md_content += (
-                self._html_converter.convert_string(html_content).markdown.strip()
+                self._html_converter.convert_string(
+                    html_content, **kwargs
+                ).markdown.strip()
                 + "\n\n"
             )
 

packages/markitdown/src/markitdown/converters/_youtube_converter.py

@@ -1,10 +1,8 @@
-import sys
 import json
 import time
-import io
 import re
 import bs4
-from typing import Any, BinaryIO, Optional, Dict, List, Union
+from typing import Any, BinaryIO, Dict, List, Union
 from urllib.parse import parse_qs, urlparse, unquote
 
 from .._base_converter import DocumentConverter, DocumentConverterResult
@@ -153,9 +151,14 @@ class YouTubeConverter(DocumentConverter):
             params = parse_qs(parsed_url.query)  # type: ignore
             if "v" in params and params["v"][0]:
                 video_id = str(params["v"][0])
+                transcript_list = ytt_api.list(video_id)
+                languages = ["en"]
+                for transcript in transcript_list:
+                    languages.append(transcript.language_code)
+                    break
                 try:
                     youtube_transcript_languages = kwargs.get(
-                        "youtube_transcript_languages", ("en",)
+                        "youtube_transcript_languages", languages
                     )
                     # Retry the transcript fetching operation
                     transcript = self._retry_operation(
@@ -165,12 +168,23 @@ class YouTubeConverter(DocumentConverter):
                         retries=3,  # Retry 3 times
                         delay=2,  # 2 seconds delay between retries
                     )
+
                     if transcript:
                         transcript_text = " ".join(
                             [part.text for part in transcript]
                         )  # type: ignore
                 except Exception as e:
-                    print(f"Error fetching transcript: {e}")
+                    # No transcript available
+                    if len(languages) == 1:
+                        print(f"Error fetching transcript: {e}")
+                    else:
+                        # Translate transcript into first kwarg
+                        transcript = (
+                            transcript_list.find_transcript(languages)
+                            .translate(youtube_transcript_languages[0])
+                            .fetch()
+                        )
+                        transcript_text = " ".join([part.text for part in transcript])
             if transcript_text:
                 webpage_text += f"\n### Transcript\n{transcript_text}\n"
 

packages/markitdown/src/markitdown/converters/_zip_converter.py

@@ -1,4 +1,3 @@
-import sys
 import zipfile
 import io
 import os

packages/markitdown/tests/_test_vectors.py

@@ -25,8 +25,11 @@ GENERAL_TEST_VECTORS = [
             "# Abstract",
             "# Introduction",
             "AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation",
+            "data:image/png;base64...",
+        ],
+        must_not_include=[
+            "data:image/png;base64,iVBORw0KGgoAAAANSU",
         ],
-        must_not_include=[],
     ),
     FileTestVector(
         filename="test.xlsx",
@@ -65,8 +68,9 @@ GENERAL_TEST_VECTORS = [
             "AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation",
             "a3f6004b-6f4f-4ea8-bee3-3741f4dc385f",  # chart title
             "2003",  # chart value
+            "![This phrase of the caption is Human-written.](Picture4.jpg)",
         ],
-        must_not_include=[],
+        must_not_include=["data:image/jpeg;base64,/9j/4AAQSkZJRgABAQE"],
     ),
     FileTestVector(
         filename="test_outlook_msg.msg",
@@ -140,10 +144,11 @@ GENERAL_TEST_VECTORS = [
         charset="cp932",
         url=None,
         must_include=[
-            "名前,年齢,住所",
-            "佐藤太郎,30,東京",
-            "三木英子,25,大阪",
-            "髙橋淳,35,名古屋",
+            "| 名前 | 年齢 | 住所 |",
+            "| --- | --- | --- |",
+            "| 佐藤太郎 | 30 | 東京 |",
+            "| 三木英子 | 25 | 大阪 |",
+            "| 髙橋淳 | 35 | 名古屋 |",
         ],
         must_not_include=[],
     ),
@@ -230,3 +235,45 @@ GENERAL_TEST_VECTORS = [
         must_not_include=[],
     ),
 ]
+
+
+DATA_URI_TEST_VECTORS = [
+    FileTestVector(
+        filename="test.docx",
+        mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document",
+        charset=None,
+        url=None,
+        must_include=[
+            "314b0a30-5b04-470b-b9f7-eed2c2bec74a",
+            "49e168b7-d2ae-407f-a055-2167576f39a1",
+            "## d666f1f7-46cb-42bd-9a39-9a39cf2a509f",
+            "# Abstract",
+            "# Introduction",
+            "AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation",
+            "data:image/png;base64,iVBORw0KGgoAAAANSU",
+        ],
+        must_not_include=[
+            "data:image/png;base64...",
+        ],
+    ),
+    FileTestVector(
+        filename="test.pptx",
+        mimetype="application/vnd.openxmlformats-officedocument.presentationml.presentation",
+        charset=None,
+        url=None,
+        must_include=[
+            "2cdda5c8-e50e-4db4-b5f0-9722a649f455",
+            "04191ea8-5c73-4215-a1d3-1cfb43aaaf12",
+            "44bf7d06-5e7a-4a40-a2e1-a2e42ef28c8a",
+            "1b92870d-e3b5-4e65-8153-919f4ff45592",
+            "AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation",
+            "a3f6004b-6f4f-4ea8-bee3-3741f4dc385f",  # chart title
+            "2003",  # chart value
+            "![This phrase of the caption is Human-written.]",  # image caption
+            "data:image/jpeg;base64,/9j/4AAQSkZJRgABAQE",
+        ],
+        must_not_include=[
+            "![This phrase of the caption is Human-written.](Picture4.jpg)",
+        ],
+    ),
+]

packages/markitdown/tests/test_cli_misc.py

@@ -1,6 +1,5 @@
 #!/usr/bin/env python3 -m pytest
 import subprocess
-import pytest
 from markitdown import __version__
 
 # This file contains CLI tests that are not directly tested by the FileTestVectors.
@@ -24,8 +23,8 @@ def test_invalid_flag() -> None:
     assert result.returncode != 0, f"CLI exited with error: {result.stderr}"
     assert (
         "unrecognized arguments" in result.stderr
-    ), f"Expected 'unrecognized arguments' to appear in STDERR"
-    assert "SYNTAX" in result.stderr, f"Expected 'SYNTAX' to appear in STDERR"
+    ), "Expected 'unrecognized arguments' to appear in STDERR"
+    assert "SYNTAX" in result.stderr, "Expected 'SYNTAX' to appear in STDERR"
 
 
 if __name__ == "__main__":

packages/markitdown/tests/test_cli_vectors.py

@@ -7,16 +7,17 @@ import locale
 from typing import List
 
 if __name__ == "__main__":
-    from _test_vectors import GENERAL_TEST_VECTORS, FileTestVector
+    from _test_vectors import (
+        GENERAL_TEST_VECTORS,
+        DATA_URI_TEST_VECTORS,
+        FileTestVector,
+    )
 else:
-    from ._test_vectors import GENERAL_TEST_VECTORS, FileTestVector
-
-from markitdown import (
-    MarkItDown,
-    UnsupportedFormatException,
-    FileConversionException,
-    StreamInfo,
-)
+    from ._test_vectors import (
+        GENERAL_TEST_VECTORS,
+        DATA_URI_TEST_VECTORS,
+        FileTestVector,
+    )
 
 skip_remote = (
     True if os.environ.get("GITHUB_ACTIONS") else False
@@ -132,8 +133,6 @@ def test_convert_url(shared_tmp_dir, test_vector):
     """Test the conversion of a stream with no stream info."""
     # Note: tmp_dir is not used here, but is needed to match the signature
 
-    markitdown = MarkItDown()
-
     time.sleep(1)  # Ensure we don't hit rate limits
     result = subprocess.run(
         ["python", "-m", "markitdown", TEST_FILES_URL + "/" + test_vector.filename],
@@ -149,13 +148,46 @@ def test_convert_url(shared_tmp_dir, test_vector):
         assert test_string not in stdout
 
 
+@pytest.mark.parametrize("test_vector", DATA_URI_TEST_VECTORS)
+def test_output_to_file_with_data_uris(shared_tmp_dir, test_vector) -> None:
+    """Test CLI functionality when keep_data_uris is enabled"""
+
+    output_file = os.path.join(shared_tmp_dir, test_vector.filename + ".output")
+    result = subprocess.run(
+        [
+            "python",
+            "-m",
+            "markitdown",
+            "--keep-data-uris",
+            "-o",
+            output_file,
+            os.path.join(TEST_FILES_DIR, test_vector.filename),
+        ],
+        capture_output=True,
+        text=True,
+    )
+
+    assert result.returncode == 0, f"CLI exited with error: {result.stderr}"
+    assert os.path.exists(output_file), f"Output file not created: {output_file}"
+
+    with open(output_file, "r") as f:
+        output_data = f.read()
+        for test_string in test_vector.must_include:
+            assert test_string in output_data
+        for test_string in test_vector.must_not_include:
+            assert test_string not in output_data
+
+    os.remove(output_file)
+    assert not os.path.exists(output_file), f"Output file not deleted: {output_file}"
+
+
 if __name__ == "__main__":
-    import sys
     import tempfile
 
     """Runs this file's tests from the command line."""
 
     with tempfile.TemporaryDirectory() as tmp_dir:
+        # General tests
         for test_function in [
             test_output_to_stdout,
             test_output_to_file,
@@ -169,4 +201,17 @@ if __name__ == "__main__":
                 )
                 test_function(tmp_dir, test_vector)
                 print("OK")
+
+        # Data URI tests
+        for test_function in [
+            test_output_to_file_with_data_uris,
+        ]:
+            for test_vector in DATA_URI_TEST_VECTORS:
+                print(
+                    f"Running {test_function.__name__} on {test_vector.filename}...",
+                    end="",
+                )
+                test_function(tmp_dir, test_vector)
+                print("OK")
+
     print("All tests passed!")

packages/markitdown/tests/test_docintel_html.py

@@ -0,0 +1,26 @@
+import io
+from markitdown.converters._doc_intel_converter import (
+    DocumentIntelligenceConverter,
+    DocumentIntelligenceFileType,
+)
+from markitdown._stream_info import StreamInfo
+
+
+def _make_converter(file_types):
+    conv = DocumentIntelligenceConverter.__new__(DocumentIntelligenceConverter)
+    conv._file_types = file_types
+    return conv
+
+
+def test_docintel_accepts_html_extension():
+    conv = _make_converter([DocumentIntelligenceFileType.HTML])
+    stream_info = StreamInfo(mimetype=None, extension=".html")
+    assert conv.accepts(io.BytesIO(b""), stream_info)
+
+
+def test_docintel_accepts_html_mimetype():
+    conv = _make_converter([DocumentIntelligenceFileType.HTML])
+    stream_info = StreamInfo(mimetype="text/html", extension=None)
+    assert conv.accepts(io.BytesIO(b""), stream_info)
+    stream_info = StreamInfo(mimetype="application/xhtml+xml", extension=None)
+    assert conv.accepts(io.BytesIO(b""), stream_info)