[MS] Add OCR layer service for embedded images and PDF scans (#1541)

* Add OCR test data and implement tests for various document formats

- Created HTML file with multiple images for testing OCR extraction.
- Added several PDF files with different layouts and image placements to validate OCR functionality.
- Introduced PPTX files with complex layouts and images at various positions for comprehensive testing.
- Included XLSX files with multiple images and complex layouts to ensure accurate OCR extraction.
- Implemented a new test suite in `test_ocr.py` to validate OCR functionality across all document types, ensuring context preservation and accuracy.

* Enhance OCR functionality and validation in document converters

- Refactor image extraction and processing in PDF, PPTX, and XLSX converters for improved readability and consistency.
- Implement detailed validation for OCR text positioning relative to surrounding text in test cases.
- Introduce comprehensive tests for expected OCR results across various document types, ensuring no base64 images are present.
- Improve error handling and logging for better debugging during OCR extraction.

* Add support for scanned PDFs with full-page OCR fallback and implement tests

* Bump version to 0.1.6b1 in __about__.py

* Refactor OCR services to support LLM Vision, update README and tests accordingly

* Add OCR-enabled converters and ensure consistent OCR format across document types

* Refactor converters to improve import organization and enhance OCR functionality across DOCX, PDF, PPTX, and XLSX converters

* Refactor exception imports for consistency across converters and tests

* Fix OCR tests to match MockOCRService output and fix cross-platform file URI handling

* Bump version to 0.1.6b1 in __about__.py

* Skip DOCX/XLSX/PPTX OCR tests when optional dependencies are missing

* Add comprehensive OCR test suite for various document formats

- Introduced multiple test documents for PDF, DOCX, XLSX, and PPTX formats, covering scenarios with images at the start, middle, and end.
- Implemented tests for complex layouts, multi-page documents, and documents with multiple images.
- Created a new test script `test_ocr.py` to validate OCR functionality, ensuring context preservation and accurate text extraction.
- Added expected OCR results for validation against ground truth.
- Included tests for scanned documents to verify OCR fallback mechanisms.

* Remove obsolete HTML test files and refactor test cases for file URIs and OCR format consistency

- Deleted `html_image_start.html` and `html_multiple_images.html` as they are no longer needed.
- Updated `test_file_uris` in `test_module_misc.py` to simplify assertions by removing unnecessary `url2pathname` usage.
- Removed `test_ocr_format_consistency.py` as it is no longer relevant to the current testing framework.

* Refactor OCR processing in PdfConverterWithOCR and enhance unit tests for multipage PDFs

* Revert

* Revert

* Update REDMEs

* Refactor import statements for consistency and improve formatting in converter and test files

README.md

@@ -9,7 +9,7 @@
 
 > [!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]'` 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.
 
@@ -132,6 +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: