Goldziher/html-to-markdown

AI Summary: Implement support for the HTML `<mark>` element in the `html-to-markdown` Python library. This involves creating a converter function to handle the `<mark>` tag, potentially adding a configuration option to select between different Markdown highlighting styles (double equals, HTML preservation, or bold), and writing comprehensive tests.

AI Summary: Implement a streaming/chunked processing mode for the HTML to Markdown converter to handle large HTML documents more efficiently, reducing memory usage and improving performance. This involves modifying the core processing logic to handle HTML in smaller chunks, ensuring context preservation across chunks, adding a streaming API with configurable chunk sizes, providing optional progress reporting, and updating the CLI and tests.

AI Summary: Implement support for HTML citation elements (`<cite>`, `<q>`) and the `cite` attribute in blockquotes within an existing HTML-to-Markdown converter. This involves creating new converters for `<cite>` and `<q>`, enhancing the existing `blockquote` converter, and adding comprehensive test cases to ensure correct handling of various scenarios, including nested citations and international quotation marks.

AI Summary: Implement support for HTML5 `<details>` and `<summary>` tags in the `html-to-markdown` Python library. This involves adding these tags to the supported element list, creating converters to preserve their structure in the output Markdown (using GitHub-flavored Markdown's `<details>` and `<summary>`), and adding comprehensive test cases to ensure correct functionality with various nested content scenarios.

AI Summary: Implement support for HTML definition lists (`<dl>`, `<dt>`, `<dd>`) in the `html-to-markdown` Python library. This involves creating converters for these elements, handling nested lists and multiple definitions per term, adding a configuration option for the output style (e.g., extended Markdown or fallback format), and writing comprehensive tests.

AI Summary: Implement support for converting HTML checkbox inputs within lists to GitHub-flavored Markdown task list syntax. This involves modifying the list item converter to detect checkboxes, check their checked state, and convert them to `- [x]` or `- [ ]` accordingly. Thorough testing is required to ensure compatibility with mixed list types and nested lists.

AI Summary: Implement support for HTML5 semantic elements (article, section, nav, aside, header, footer, main) in the `html-to-markdown` Python library. This involves adding these elements to the supported elements list, creating appropriate converters to handle them as block containers with proper spacing, and adding comprehensive test coverage. Consider adding optional comment markers to preserve semantic meaning in the Markdown output.