@gaiaverse/semantic-turning-point-detector/dist/stripContent.d.ts

Detects key semantic turning points in conversations using recursive semantic distance analysis. Ideal for conversation analysis, dialogue segmentation, insight detection, and AI-assisted reasoning tasks.

import { Message } from "./Message";
import { TurningPointDetectorConfig } from "./types";
/**
 * Defines the formatting style for replaced headings.
 * - 'plain': Just the heading text (removes '#' markers only).
 * - 'bold': Surrounds the heading text with '**'.
 * - 'italic': Surrounds the heading text with '*'.
 * - 'bold-italic': Surrounds the heading text with '***'.
 * - 'prefix': Prepends a specific string (defined in `headingPrefix`) to the heading text.
 */
export type HeadingStyle = 'plain' | 'bold' | 'italic' | 'bold-italic' | 'prefix';
/**
 * Configuration options for selectivelyStripMarkdown function.
 */
export type StripMarkdownOptions = {
    /**
     * If true, removes list markers (*, -, +, 1.) while keeping the item text.
     * @default false
     */
    removeLists?: boolean;
    /**
     * Defines how heading syntax (#) should be replaced.
     * @default 'bold'
     */
    headingStyle?: HeadingStyle;
    /**
     * The prefix string to use when `headingStyle` is 'prefix'.
     * @default 'heading: '
     */
    headingPrefix?: string;
};
/**
 * Selectively removes or reformats Markdown elements like headings and optionally lists.
 * Headings (#) are replaced based on the specified `headingStyle`.
 * Lists (*, -, +, 1.) can optionally be stripped to plain text (controlled by `removeLists`).
 * Content remains on the same line, and overall newlines are preserved.
 *
 * @param markdown The input Markdown string.
 * @param options Configuration options for stripping and formatting.
 * @returns The processed string.
 */
export declare function selectivelyStripMarkdown(markdown: string, options?: StripMarkdownOptions): string;
/**
 * A helper function that formats a given message in a form that ensures the content is not long and easily distinguishable as part of contextual information when requesting a llm or nlp model to process it.
 * @param semanticSettings
 * @param m
 * @param dimension
 * @param addHeader
 * @param sliceId
 * @returns
 */
export declare function returnFormattedMessageContent(semanticSettings: Partial<TurningPointDetectorConfig>, m: Message, dimension?: number, addHeader?: boolean, sliceId?: boolean): string;
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