/**
 * @fileoverview Utility for splitting text into semantic chunks for RAG and NLP tasks.
 * Uses complex regex patterns to identify structural elements like lists, tables, and code.
 *
 * ### Split Text by Semantic Characters
 * <img width="350px"  src="https://i.imgur.com/RpXf5as.png" />
 *
 *
 * Splits document text into semantic chunks based on various textual and structural
    * elements like HTML, markdown, and paragraphs.
 *
 * This function performs a comprehensive tokenization of the input text, considering a wide range
    * of semantic elements and structural patterns commonly found in documents.It uses regular
        * expressions to identify and separate the following elements:
 *
 * 1. Headings(Setext - style, Markdown, and HTML - style)
    * 2. Citations(e.g., [1])
        * 3. List items(bulleted, numbered, lettered, or task lists, including nested up to three levels)
            * 4. Block quotes(including nested quotes and citations, up to three levels)
                * 5. Code blocks(fenced, indented, or HTML pre / code tags)
                    * 6. Tables(Markdown, grid tables, and HTML tables)
                        * 7. Horizontal rules(Markdown and HTML hr tag)
                            * 8. Standalone lines or phrases(including single - line blocks and HTML elements)
                                * 9. Sentences or phrases ending with punctuation(including ellipsis and Unicode punctuation)
                                * 10. Quoted text, parenthetical phrases, or bracketed content
                                    * 11. Paragraphs
                                        * 12. HTML - like tags and their content(including self - closing tags and attributes)
                                            * 13. LaTeX - style math expressions(inline and block)
                                                * 14. Any remaining content(fallback)
                                                    *
 * The function applies various length constraints to each type of element to ensure reasonable
    * chunk sizes.It also handles nested structures and special cases like code blocks and math
        * expressions.
 *
 * [Sentence RAG Benchmarks](https://superlinked.com/vectorhub/articles/evaluation-rag-retrieval-chunking-methods)
 *
 * @author[Jina AI(2024)](https://gist.github.com/hanxiao/3f60354cf6dc5ac698bc9154163b4e6a)
            * @param { string } text - The input text to be split into semantic chunks.
 * @param { Object }[options = {}] - Optional configuration options(currently unused).
 * @returns { Array.<string> } An array of text chunks, each representing a semantic unit of the document.
 * @category Topics
        * @example
        * const text = "# Heading\n\nThis is a paragraph.\n\n- List item 1\n- List item 2\n\n";
 * const chunks = splitTextSemanticChars(text);
 * console.log(chunks);
 * // Output: ['# Heading', 'This is a paragraph.', '- List item 1', '- List item 2']
 */
export declare function splitTextSemanticChars(text: any, options?: {}): unknown[];