Security/Logic Fix: Autonomous Code Review

[fliptrigga13]

Autonomous Bug Report & Patch

This vulnerability and fix were autonomously discovered by the Lucy Red Team swarm.

The provided code snippet is an enhanced DOCX converter with OCR support for embedded images. It extracts images from Word documents and performs OCR while maintaining the document flow. However, there are several potential issues and improvements that can be made to ensure the robustness and correctness of the implementation.

One critical bug or issue is related to the handling of the ocr_service and its availability. The code checks for the presence of the ocr_service but does not handle cases where the OCR service might fail or return unexpected results. This could lead to incomplete or incorrect Markdown output.

Here are some steps to address this issue:

1. Error Handling for OCR Service: Ensure that any errors from the OCR service are properly handled and logged.
2. Validation of OCR Results: Validate the results returned by the OCR service to ensure they are not empty or contain unexpected data.

Let's add some error handling and validation around the OCR service usage:

class DocxConverterWithOCR(HtmlConverter):
    # ... (existing code)

    def _extract_and_ocr_images(self, file_stream: BinaryIO, ocr_service: LLMVisionOCRService) -> dict:
        # Placeholder for actual image extraction and OCR logic
        image_ocr_map = {}
        try:
            # Extract images from the DOCX file
            document = Document(file_stream)
            for i, paragraph in enumerate(document.paragraphs):
                for run in paragraph.runs:
                    if run._element.tag.endswith