/** @jsxImportSource https://esm.sh/react */ import React, { useState } from "https://esm.sh/react"; import { createRoot } from "https://esm.sh/react-dom/client"; // Types for structured API response interface ResearchResult { title: string; summary: string; sources: Array<{ url: string; title: string }>; keyPoints: string[]; } function ResearchTool() { const [query, setQuery] = useState(''); const [results, setResults] = useState(null); const [loading, setLoading] = useState(false); const [error, setError] = useState(null); const handleSearch = async (e: React.FormEvent) => { e.preventDefault(); setLoading(true); setError(null); setResults(null); try { const response = await fetch('/research', { method: 'POST', headers: { 'Content-Type': 'application/json' }, body: JSON.stringify({ query }) }); if (!response.ok) { throw new Error('Research request failed'); } const data = await response.json(); setResults(data); } catch (err) { setError(err instanceof Error ? err.message : 'An unknown error occurred'); } finally { setLoading(false); } }; return (

🔍 AI Research Assistant

{loading &&

🌀 Researching...

} {error && (

⚠️ {error}

)} {results && (

{results.title}

{results.summary}

Key Points

{point}

Sources

{results.sources.map((source, index) => ( {source.title} ))}

)} View Source

); } function client() { createRoot(document.getElementById('root')).render(); } if (typeof document !== 'undefined') { client(); } export default async function server(request: Request): Promise { // Server-side research handler if (request.method === 'POST' && new URL(request.url).pathname === '/research') { try { const { query } = await request.json(); // Simulated Perplexity API call (replace with actual API integration) const mockResult: ResearchResult = { title: `Research on: ${query}`, summary: 'A comprehensive overview of your research query.', keyPoints: [ 'First key insight about the topic', 'Second important finding', 'Third significant observation' ], sources: [ { url: 'https://example.com/source1', title: 'Source 1' }, { url: 'https://example.com/source2', title: 'Source 2' } ] }; return new Response(JSON.stringify(mockResult), { headers: { 'Content-Type': 'application/json' } }); } catch (error) { return new Response(JSON.stringify({ error: 'Research failed' }), { status: 500, headers: { 'Content-Type': 'application/json' } }); } } // Initial page load return new Response(` AI Research Assistant

`, { headers: { 'Content-Type': 'text/html' } }); } const css = ` body { font-family: 'Arial', sans-serif; max-width: 800px; margin: 0 auto; padding: 20px; line-height: 1.6; background-color: #f4f4f4; } .research-container { background: white; border-radius: 8px; padding: 20px; box-shadow: 0 4px 6px rgba(0,0,0,0.1); } .search-form { display: flex; margin-bottom: 20px; } input { flex-grow: 1; padding: 10px; border: 1px solid #ddd; border-radius: 4px; } button { padding: 10px 15px; background-color: #007bff; color: white; border: none; border-radius: 4px; margin-left: 10px; } button:disabled { background-color: #cccccc; } .loading { text-align: center; color: #007bff; } .error-message { color: red; text-align: center; } .results-container h2 { color: #333; border-bottom: 2px solid #007bff; } .sources a { display: block; color: #0066cc; text-decoration: none; margin: 5px 0; } .source-link { display: block; text-align: center; margin-top: 20px; color: #666; text-decoration: none; } @media (max-width: 600px) { .search-form { flex-direction: column; } button { margin-left: 0; margin-top: 10px; } } `;

respectfulMagentaQuelea