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

Requires markitdown>=0.1.8,<0.2.0, which provides the Office image-rendering hooks used by this plugin. Installing the plugin automatically resolves a compatible core version.

pip install markitdown-ocr

The plugin uses whatever OpenAI-compatible client you already have. Install one if you don't have it yet:

pip install openai

Usage

Command Line

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:

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:

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:

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:

MarkItDown discovers the plugin via the markitdown.plugin entry point group
It calls register_converters(), forwarding all kwargs including llm_client and llm_model
The plugin creates an LLMVisionOCRService from those kwargs
Four OCR-enhanced converters are registered at priority -1.0 — before the built-in converters at priority 0.0

When a file is converted:

The OCR converter accepts the file
It extracts embedded images from the document
Each image is sent to the LLM with an extraction prompt
The returned text is placed alongside document content (XLSX images follow their sheet's table)
If the LLM call fails, conversion continues without that image's text

The DOCX, PPTX, and XLSX converters subclass their core counterparts and override the same semi-private _image_to_html method. Core handles native content, preprocessing, and placement; the plugin supplies escaped OCR HTML, which passes through the shared HTML-to-Markdown renderer. PDF uses its separate existing pipeline.

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

Inherits core DOCX preprocessing, styles, math, and Mammoth conversion.
Mammoth provides each embedded image to _image_to_html. OCR fragments are inserted into the document's HTML before Markdown rendering, not substituted into finished Markdown.
Block fragments split enclosing paragraphs where necessary and remain inside their table cell or list item. Table-cell line breaks follow the shared HTML converter's existing limitations.

PPTX

Picture shapes, placeholder shapes with images, and images inside groups are all supported.
Inherits core shape ordering, native text, tables, charts, and speaker notes.
Slide content now uses the core converter's real line breaks rather than the old plugin's literal \n text, and inherits its empty-title and empty-notes handling.
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

Inherits core workbook repair and table rendering; images are read from the same repaired workbook.
Images are listed under a ### Images in this sheet: section after the sheet's data table — they are not interleaved into the table rows.
Sheet heading spacing follows the core converter; no new cell-position labels are added.
Legacy .xls files remain handled by the existing core converter, without image OCR.

Output format

Every extracted OCR block is wrapped as:

*[Image OCR]
<extracted text>
[End OCR]*

For Office formats, recognized text is escaped as literal HTML text before Markdown rendering. Markdown escaping and line breaks therefore follow the shared HTML converter: for example, underscores may be backslash-escaped, and direct converter results use Markdown hard breaks. MarkItDown subsequently strips trailing whitespace from each output line. Empty recognition retains the native image representation (XLSX normally omits images).

Repeated image bytes are recognized once per conversion, while the result is placed at every occurrence. The cache is not shared across documents or service overrides.

Troubleshooting

OCR text missing from output

The most likely cause is a missing llm_client or llm_model. Verify:

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:

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.

For Office OCR, a service-reported error emits a warning and retains native image rendering. Exceptions raised by custom OCR services propagate from direct converter calls; MarkItDown can retry another applicable converter through its normal fallback behavior.

Development

Running Tests

cd packages/markitdown-ocr
pytest tests/ -v

Building from Source

git clone https://github.com/microsoft/markitdown.git
cd markitdown
pip install -e 'packages/markitdown[docx,pptx,xlsx]' -e packages/markitdown-ocr

Contributing

Contributions are welcome! See the MarkItDown repository for guidelines.

License

MIT — see 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)