/**
 * Glossary service for parsing and looking up Jamf documentation glossary terms
 *
 * Uses Fluid Topics API on learn.jamf.com:
 * - GET /api/khub/maps/{mapId}/toc — list all glossary terms
 * - GET /api/khub/maps/{mapId}/topics/{contentId}/content — term HTML
 *
 * Jamf's glossary uses DITA glossentry format where each term is a separate topic:
 *   <div class="glossdef"><p>Definition text</p></div>
 *
 * Also supports fallback formats:
 * - Definition list (<dl>/<dt>/<dd>)
 * - Heading + paragraph (h2/h3 followed by <p>)
 *
 * Uses fuse.js for fuzzy ranking of collected entries.
 */
import { type ProductId, type LocaleId } from '../constants.js';
import type { GlossaryEntry, GlossaryLookupResult } from '../types.js';
import type { ServerContext } from '../types/context.js';
/**
 * Parse glossary entries from HTML content.
 *
 * Priority order:
 * 1. DITA glossentry format (h1.glossterm + .glossdef) — Jamf's actual format
 * 2. Definition list (<dl>/<dt>/<dd>)
 * 3. Heading + paragraph (h2/h3 followed by <p>)
 * 4. Fallback: h1 title + article body content
 */
export declare function parseGlossaryEntries(html: string, sourceUrl: string, product?: string): GlossaryEntry[];
/**
 * Search for matching glossary entries using fuse.js fuzzy matching.
 * Used to rank and filter entries collected from multiple glossary pages.
 */
export declare function searchGlossaryEntries(entries: GlossaryEntry[], term: string): GlossaryEntry[];
/**
 * Look up a glossary term across Jamf documentation.
 *
 * Strategy:
 * 1. Fetch glossary TOC from Fluid Topics API (cached)
 * 2. Fuzzy-match term against TOC titles
 * 3. Fetch and parse matching glossary topics
 * 4. Rank results with fuse.js and apply token limit
 */
export declare function lookupGlossaryTerm(ctx: ServerContext, params: {
    term: string;
    product?: ProductId | undefined;
    language?: LocaleId | undefined;
    maxTokens?: number | undefined;
}): Promise<GlossaryLookupResult>;
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