mirror of
https://github.com/github/awesome-copilot.git
synced 2026-02-20 02:15:12 +00:00
- Add static website with pages for agents, prompts, instructions, skills, and collections - Implement client-side fuzzy search across all resources - Add file viewer modal with copy-to-clipboard and install-to-editor functionality - Add Tools page for MCP server and future tools - Add Samples page placeholder for copilot-sdk cookbook migration - Add metadata JSON generation script (eng/generate-website-data.mjs) - Add GitHub Actions workflow for automated Pages deployment - Update package.json with website build scripts
140 lines
3.6 KiB
JavaScript
140 lines
3.6 KiB
JavaScript
/**
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* Fuzzy search implementation for the Awesome Copilot website
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* Simple substring matching on title and description with scoring
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*/
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class FuzzySearch {
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constructor(items = []) {
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this.items = items;
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}
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/**
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* Update the items to search
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*/
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setItems(items) {
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this.items = items;
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}
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/**
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* Search items with fuzzy matching
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* @param {string} query - The search query
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* @param {object} options - Search options
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* @returns {array} Matching items sorted by relevance
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*/
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search(query, options = {}) {
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const {
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fields = ['title', 'description', 'searchText'],
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limit = 50,
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minScore = 0,
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} = options;
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if (!query || query.trim().length === 0) {
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return this.items.slice(0, limit);
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}
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const normalizedQuery = query.toLowerCase().trim();
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const queryWords = normalizedQuery.split(/\s+/);
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const results = [];
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for (const item of this.items) {
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const score = this.calculateScore(item, queryWords, fields);
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if (score > minScore) {
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results.push({ item, score });
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}
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}
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// Sort by score descending
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results.sort((a, b) => b.score - a.score);
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return results.slice(0, limit).map(r => r.item);
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}
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/**
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* Calculate match score for an item
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*/
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calculateScore(item, queryWords, fields) {
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let totalScore = 0;
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for (const word of queryWords) {
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let wordScore = 0;
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for (const field of fields) {
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const value = item[field];
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if (!value) continue;
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const normalizedValue = String(value).toLowerCase();
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// Exact match in title gets highest score
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if (field === 'title' && normalizedValue === word) {
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wordScore = Math.max(wordScore, 100);
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}
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// Title starts with word
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else if (field === 'title' && normalizedValue.startsWith(word)) {
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wordScore = Math.max(wordScore, 80);
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}
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// Title contains word
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else if (field === 'title' && normalizedValue.includes(word)) {
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wordScore = Math.max(wordScore, 60);
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}
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// Description contains word
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else if (field === 'description' && normalizedValue.includes(word)) {
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wordScore = Math.max(wordScore, 30);
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}
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// searchText (includes tags, tools, etc) contains word
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else if (field === 'searchText' && normalizedValue.includes(word)) {
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wordScore = Math.max(wordScore, 20);
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}
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}
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totalScore += wordScore;
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}
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// Bonus for matching all words
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const matchesAllWords = queryWords.every(word =>
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fields.some(field => {
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const value = item[field];
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return value && String(value).toLowerCase().includes(word);
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})
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);
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if (matchesAllWords && queryWords.length > 1) {
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totalScore *= 1.5;
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}
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return totalScore;
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}
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/**
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* Highlight matching text in a string
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*/
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highlight(text, query) {
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if (!query || !text) return escapeHtml(text || '');
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const normalizedQuery = query.toLowerCase().trim();
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const words = normalizedQuery.split(/\s+/);
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let result = escapeHtml(text);
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for (const word of words) {
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if (word.length < 2) continue;
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const regex = new RegExp(`(${word.replace(/[.*+?^${}()|[\]\\]/g, '\\$&')})`, 'gi');
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result = result.replace(regex, '<mark>$1</mark>');
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}
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return result;
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}
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}
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// Global search instance
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const globalSearch = new FuzzySearch();
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/**
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* Initialize global search with search index
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*/
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async function initGlobalSearch() {
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const searchIndex = await fetchData('search-index.json');
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if (searchIndex) {
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globalSearch.setItems(searchIndex);
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}
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return globalSearch;
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}
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