Major changes
This commit is contained in:
owenqwenstarsky
@@ -0,0 +1,252 @@
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import { NextRequest } from 'next/server';
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import { prisma } from '@/lib/db';
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interface WikipediaSummary {
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title: string;
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extract: string;
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thumbnail?: { source: string };
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originalimage?: { source: string };
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}
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interface WikiParseResult {
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parse: {
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title: string;
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text: { '*': string };
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images: string[];
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};
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}
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async function getWikipediaSummary(title: string): Promise<WikipediaSummary | null> {
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try {
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const apiTitle = title.replace(/%20/g, '_');
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const response = await fetch(
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`https://en.wikipedia.org/api/rest_v1/page/summary/${apiTitle}`,
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{
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headers: { 'User-Agent': 'WikiPlus/1.0' },
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}
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);
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if (!response.ok) return null;
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return await response.json();
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} catch {
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return null;
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}
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}
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async function getWikipediaContent(title: string): Promise<{ text: string; images: string[] } | null> {
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try {
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const apiTitle = title.replace(/%20/g, '_');
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const response = await fetch(
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`https://en.wikipedia.org/w/api.php?action=parse&page=${encodeURIComponent(apiTitle)}&format=json&prop=text|images&disableeditsection=true&redirects=true`,
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{
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headers: { 'User-Agent': 'WikiPlus/1.0' },
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}
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);
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if (!response.ok) return null;
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const data: WikiParseResult = await response.json();
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if (!data.parse) return null;
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// Extract plain text from HTML
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const html = data.parse.text?.['*'] || '';
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const plainText = html
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.replace(/<style[^>]*>[\s\S]*?<\/style>/gi, '')
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.replace(/<script[^>]*>[\s\S]*?<\/script>/gi, '')
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.replace(/<[^>]+>/g, ' ')
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.replace(/ /g, ' ')
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.replace(/&/g, '&')
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.replace(/</g, '<')
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.replace(/>/g, '>')
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.replace(/"/g, '"')
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.replace(/'/g, "'")
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.replace(/\s+/g, ' ')
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.trim();
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// Get image URLs
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const images = (data.parse.images || [])
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.filter((img: string) => !img.includes('icon') && !img.includes('logo') && !img.includes('Commons-logo'))
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.slice(0, 5)
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.map((img: string) => `https://en.wikipedia.org/wiki/Special:FilePath/${encodeURIComponent(img)}`);
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return { text: plainText.slice(0, 15000), images };
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} catch {
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return null;
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}
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}
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export async function GET(request: NextRequest) {
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const searchParams = request.nextUrl.searchParams;
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const title = searchParams.get('title');
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if (!title) {
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return new Response('Missing title parameter', { status: 400 });
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}
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// Normalize the slug for database lookup
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const slug = title.replace(/%20/g, '_').replace(/ /g, '_');
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// Check if article exists in database
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const existingArticle = await prisma.article.findUnique({
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where: { slug },
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});
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if (existingArticle) {
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// Return cached article wrapped in <article> tags
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const cachedContent = `<article>${existingArticle.content}</article>`;
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return new Response(cachedContent, {
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headers: {
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'Content-Type': 'text/plain; charset=utf-8',
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'X-Cache': 'HIT',
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},
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});
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}
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const apiKey = process.env.OPENROUTER_API_KEY;
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if (!apiKey) {
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return new Response('OpenRouter API key not configured', { status: 500 });
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}
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// Fetch Wikipedia data
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const [summary, content] = await Promise.all([
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getWikipediaSummary(title),
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getWikipediaContent(title),
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]);
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if (!summary || !content) {
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return new Response('Article not found', { status: 404 });
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}
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const imageUrl = summary.thumbnail?.source || summary.originalimage?.source;
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const imageContext = imageUrl
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? `\n\nMain image available: ${imageUrl}\nAdditional images: ${content.images.join(', ')}`
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: content.images.length > 0
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? `\n\nImages available: ${content.images.join(', ')}`
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: '';
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const systemPrompt = `You are an expert writer creating comprehensive, in-depth articles for an AI-powered Wikipedia alternative. Your goal is to transform encyclopedia content into rich, detailed, and engaging prose that thoroughly covers the topic.
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Guidelines:
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- Write a COMPREHENSIVE and DETAILED article - aim for depth and thoroughness
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- Cover ALL major aspects of the topic: history, significance, key details, related concepts, and impact
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- Use markdown formatting extensively:
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- Use ## for main sections and ### for subsections
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- Use **bold** for key terms and *italic* for emphasis
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- Use bullet lists and numbered lists where appropriate
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- Use > blockquotes for notable quotes or key facts
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- Include the main image at the top using markdown: 
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- Structure the article with multiple well-developed sections (5-8 sections minimum)
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- Each section should have multiple paragraphs with detailed explanations
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- Add context that helps readers understand why this topic matters
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- Include interesting facts, historical context, and connections to broader themes
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- Maintain factual accuracy - expand on the source material but don't invent facts
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- Write at least 1000-1500 words for a thorough treatment of the topic
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- Output ONLY the article content wrapped in <article></article> tags
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- Do not include any text outside the <article> tags`;
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const userPrompt = `Write a comprehensive, detailed article about "${summary.title}" based on this Wikipedia content:
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Summary: ${summary.extract}
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Full content: ${content.text}${imageContext}
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Requirements:
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- Write a THOROUGH article with 5-8 well-developed sections minimum
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- Each section should have multiple detailed paragraphs
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- Cover history, significance, key facts, and broader context
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- Use rich markdown formatting throughout
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- Aim for 1000-1500+ words total
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- Output in markdown wrapped in <article></article> tags`;
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// Call OpenRouter API with streaming
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const openRouterResponse = await fetch('https://openrouter.ai/api/v1/chat/completions', {
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method: 'POST',
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headers: {
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'Authorization': `Bearer ${apiKey}`,
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'Content-Type': 'application/json',
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},
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body: JSON.stringify({
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model: 'minimax/minimax-m2.1',
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messages: [
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{ role: 'system', content: systemPrompt },
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{ role: 'user', content: userPrompt },
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],
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stream: true,
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}),
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});
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if (!openRouterResponse.ok) {
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const error = await openRouterResponse.text();
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console.error('OpenRouter error:', error);
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return new Response('Failed to generate article', { status: 500 });
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}
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// Transform the OpenRouter SSE stream to extract content and save to DB
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const encoder = new TextEncoder();
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const decoder = new TextDecoder();
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let fullContent = '';
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const transformStream = new TransformStream({
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async transform(chunk, controller) {
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const text = decoder.decode(chunk);
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const lines = text.split('\n');
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for (const line of lines) {
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if (line.startsWith('data: ')) {
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const data = line.slice(6);
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if (data === '[DONE]') {
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continue;
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}
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try {
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const parsed = JSON.parse(data);
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const contentChunk = parsed.choices?.[0]?.delta?.content;
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if (contentChunk) {
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fullContent += contentChunk;
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controller.enqueue(encoder.encode(contentChunk));
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}
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} catch {
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// Skip invalid JSON
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}
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}
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}
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},
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async flush() {
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// Extract content between <article> tags and save to database
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const articleMatch = fullContent.match(/<article>([\s\S]*?)<\/article>/);
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const articleContent = articleMatch ? articleMatch[1].trim() : fullContent;
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if (articleContent) {
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try {
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const newArticle = await prisma.article.create({
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data: {
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slug,
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title: summary.title,
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content: articleContent,
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imageUrl: imageUrl || null,
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},
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});
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// Create initial history entry
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await prisma.articleHistory.create({
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data: {
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articleId: newArticle.id,
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oldContent: '',
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newContent: articleContent,
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reason: 'Initial article',
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},
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});
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} catch (error) {
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console.error('Failed to save article to database:', error);
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}
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}
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},
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});
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const stream = openRouterResponse.body?.pipeThrough(transformStream);
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return new Response(stream, {
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headers: {
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'Content-Type': 'text/plain; charset=utf-8',
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'Transfer-Encoding': 'chunked',
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'Cache-Control': 'no-cache',
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'X-Cache': 'MISS',
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},
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});
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}
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@@ -0,0 +1,34 @@
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import { NextRequest, NextResponse } from 'next/server';
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import { prisma } from '@/lib/db';
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export async function GET(
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request: NextRequest,
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{ params }: { params: Promise<{ slug: string }> }
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) {
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const { slug } = await params;
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// Fetch article to get its ID
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const article = await prisma.article.findUnique({
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where: { slug },
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select: { id: true },
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});
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if (!article) {
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return NextResponse.json({ error: 'Article not found' }, { status: 404 });
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}
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// Fetch history entries
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const history = await prisma.articleHistory.findMany({
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where: { articleId: article.id },
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orderBy: { createdAt: 'desc' },
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select: {
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id: true,
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oldContent: true,
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newContent: true,
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reason: true,
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createdAt: true,
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},
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});
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return NextResponse.json(history);
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}
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@@ -0,0 +1,147 @@
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import { NextRequest } from 'next/server';
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import { prisma } from '@/lib/db';
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import * as Diff from 'diff';
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function generateDiffText(oldContent: string, newContent: string): string {
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const changes = Diff.diffLines(oldContent, newContent);
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const diffLines: string[] = [];
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for (const change of changes) {
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const lines = change.value.split('\n').filter(line => line !== '');
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for (const line of lines) {
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if (change.added) {
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diffLines.push(`+ ${line}`);
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} else if (change.removed) {
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diffLines.push(`- ${line}`);
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}
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}
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}
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return diffLines.join('\n');
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}
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export async function POST(
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request: NextRequest,
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{ params }: { params: Promise<{ slug: string }> }
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) {
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const { slug } = await params;
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const body = await request.json();
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const { newContent } = body;
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if (!newContent || typeof newContent !== 'string') {
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return new Response('Missing newContent', { status: 400 });
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}
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// Fetch current article
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const article = await prisma.article.findUnique({
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where: { slug },
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});
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if (!article) {
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return new Response('Article not found', { status: 404 });
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}
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const apiKey = process.env.OPENROUTER_API_KEY;
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if (!apiKey) {
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return new Response('OpenRouter API key not configured', { status: 500 });
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}
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// Generate diff between old and new content
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const diffText = generateDiffText(article.content, newContent);
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const systemPrompt = `You are an article edit reviewer. Your job is to evaluate proposed changes (diffs) to articles.
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You will be given:
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1. The current article content (assume this is factually correct and the source of truth)
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2. A diff showing the proposed changes (lines starting with "-" are removed, lines starting with "+" are added)
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Evaluate ONLY the changes based on:
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1. **Consistency** - Do the edits contradict or conflict with the existing article content?
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2. **Quality** - Is the new/modified text well-written and grammatically correct?
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3. **Relevance** - Are the changes relevant to the article topic?
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4. **Appropriateness** - Is the content appropriate (no spam, vandalism, offensive content)?
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Do NOT fact-check against external knowledge. Assume the original article is correct and evaluate whether the edits are consistent with it.
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After your evaluation, you MUST output your decision in this exact format:
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<action approve="true" reason="Your brief reason for approval" />
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OR
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<action approve="false" reason="Your brief reason for rejection" />
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Be constructive in your feedback. If rejecting, explain what could be improved.`;
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const userPrompt = `Please review the following article edit:
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**Current Article:**
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${article.content.slice(0, 6000)}
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**Proposed Changes (diff):**
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\`\`\`diff
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${diffText}
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\`\`\`
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Evaluate only the changes shown in the diff and provide your decision.`;
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// Call OpenRouter API with streaming
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const openRouterResponse = await fetch('https://openrouter.ai/api/v1/chat/completions', {
|
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method: 'POST',
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headers: {
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'Authorization': `Bearer ${apiKey}`,
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'Content-Type': 'application/json',
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},
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body: JSON.stringify({
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model: 'openai/gpt-oss-120b',
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messages: [
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{ role: 'system', content: systemPrompt },
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{ role: 'user', content: userPrompt },
|
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],
|
||||
stream: true,
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||||
}),
|
||||
});
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|
||||
if (!openRouterResponse.ok) {
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const error = await openRouterResponse.text();
|
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console.error('OpenRouter error:', error);
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return new Response('Failed to review article', { status: 500 });
|
||||
}
|
||||
|
||||
// Transform the OpenRouter SSE stream
|
||||
const encoder = new TextEncoder();
|
||||
const decoder = new TextDecoder();
|
||||
|
||||
const transformStream = new TransformStream({
|
||||
async transform(chunk, controller) {
|
||||
const text = decoder.decode(chunk);
|
||||
const lines = text.split('\n');
|
||||
|
||||
for (const line of lines) {
|
||||
if (line.startsWith('data: ')) {
|
||||
const data = line.slice(6);
|
||||
if (data === '[DONE]') {
|
||||
continue;
|
||||
}
|
||||
try {
|
||||
const parsed = JSON.parse(data);
|
||||
const contentChunk = parsed.choices?.[0]?.delta?.content;
|
||||
if (contentChunk) {
|
||||
controller.enqueue(encoder.encode(contentChunk));
|
||||
}
|
||||
} catch {
|
||||
// Skip invalid JSON
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
});
|
||||
|
||||
const stream = openRouterResponse.body?.pipeThrough(transformStream);
|
||||
|
||||
return new Response(stream, {
|
||||
headers: {
|
||||
'Content-Type': 'text/plain; charset=utf-8',
|
||||
'Transfer-Encoding': 'chunked',
|
||||
'Cache-Control': 'no-cache',
|
||||
},
|
||||
});
|
||||
}
|
||||
@@ -0,0 +1,58 @@
|
||||
import { NextRequest, NextResponse } from 'next/server';
|
||||
import { prisma } from '@/lib/db';
|
||||
|
||||
export async function POST(
|
||||
request: NextRequest,
|
||||
{ params }: { params: Promise<{ slug: string }> }
|
||||
) {
|
||||
const { slug } = await params;
|
||||
|
||||
const body = await request.json();
|
||||
const { newContent, reason } = body;
|
||||
|
||||
if (!newContent || typeof newContent !== 'string') {
|
||||
return NextResponse.json({ error: 'Missing newContent' }, { status: 400 });
|
||||
}
|
||||
|
||||
if (!reason || typeof reason !== 'string') {
|
||||
return NextResponse.json({ error: 'Missing reason' }, { status: 400 });
|
||||
}
|
||||
|
||||
// Fetch current article
|
||||
const article = await prisma.article.findUnique({
|
||||
where: { slug },
|
||||
});
|
||||
|
||||
if (!article) {
|
||||
return NextResponse.json({ error: 'Article not found' }, { status: 404 });
|
||||
}
|
||||
|
||||
// Transaction: create history entry and update article
|
||||
const result = await prisma.$transaction(async (tx) => {
|
||||
// Create history entry
|
||||
const historyEntry = await tx.articleHistory.create({
|
||||
data: {
|
||||
articleId: article.id,
|
||||
oldContent: article.content,
|
||||
newContent: newContent,
|
||||
reason: reason,
|
||||
},
|
||||
});
|
||||
|
||||
// Update article content
|
||||
await tx.article.update({
|
||||
where: { id: article.id },
|
||||
data: {
|
||||
content: newContent,
|
||||
updatedAt: new Date(),
|
||||
},
|
||||
});
|
||||
|
||||
return historyEntry;
|
||||
});
|
||||
|
||||
return NextResponse.json({
|
||||
success: true,
|
||||
historyId: result.id,
|
||||
});
|
||||
}
|
||||
@@ -0,0 +1,36 @@
|
||||
import { NextResponse } from 'next/server';
|
||||
import type { WikipediaTopic } from '@/lib/types';
|
||||
|
||||
export async function GET() {
|
||||
try {
|
||||
const response = await fetch(
|
||||
'https://en.wikipedia.org/api/rest_v1/page/random/summary',
|
||||
{
|
||||
headers: {
|
||||
'User-Agent': 'TeachMeSomethingNew/1.0',
|
||||
},
|
||||
}
|
||||
);
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error('Failed to fetch from Wikipedia API');
|
||||
}
|
||||
|
||||
const data = await response.json();
|
||||
|
||||
const topic: WikipediaTopic = {
|
||||
title: data.title,
|
||||
extract: data.extract,
|
||||
imageUrl: data.thumbnail?.source || data.originalimage?.source,
|
||||
pageUrl: data.content_urls?.desktop?.page,
|
||||
};
|
||||
|
||||
return NextResponse.json(topic);
|
||||
} catch (error) {
|
||||
console.error('Error fetching random topic:', error);
|
||||
return NextResponse.json(
|
||||
{ error: 'Failed to fetch random topic' },
|
||||
{ status: 500 }
|
||||
);
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,94 @@
|
||||
import { NextRequest, NextResponse } from 'next/server';
|
||||
import { prisma } from '@/lib/db';
|
||||
|
||||
export interface SearchResult {
|
||||
title: string;
|
||||
description: string;
|
||||
thumbnail?: string;
|
||||
}
|
||||
|
||||
export async function GET(request: NextRequest) {
|
||||
const searchParams = request.nextUrl.searchParams;
|
||||
const query = searchParams.get('query');
|
||||
|
||||
if (!query) {
|
||||
return NextResponse.json(
|
||||
{ error: 'Query parameter is required' },
|
||||
{ status: 400 }
|
||||
);
|
||||
}
|
||||
|
||||
try {
|
||||
// Use the Wikipedia Action API for search
|
||||
const response = await fetch(
|
||||
`https://en.wikipedia.org/w/api.php?action=query&list=search&srsearch=${encodeURIComponent(query)}&srlimit=20&format=json&origin=*`,
|
||||
{
|
||||
headers: {
|
||||
'User-Agent': 'WikiPlus/1.0',
|
||||
},
|
||||
}
|
||||
);
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error('Failed to fetch from Wikipedia API');
|
||||
}
|
||||
|
||||
const data = await response.json();
|
||||
|
||||
// Get page IDs for thumbnail fetching
|
||||
const searchResults = data.query?.search || [];
|
||||
const pageIds = searchResults.map((r: { pageid: number }) => r.pageid).join('|');
|
||||
|
||||
// Fetch thumbnails for results
|
||||
let thumbnails: Record<string, string> = {};
|
||||
if (pageIds) {
|
||||
const thumbResponse = await fetch(
|
||||
`https://en.wikipedia.org/w/api.php?action=query&pageids=${pageIds}&prop=pageimages&pithumbsize=200&format=json&origin=*`,
|
||||
{
|
||||
headers: {
|
||||
'User-Agent': 'WikiPlus/1.0',
|
||||
},
|
||||
}
|
||||
);
|
||||
if (thumbResponse.ok) {
|
||||
const thumbData = await thumbResponse.json();
|
||||
const pages = thumbData.query?.pages || {};
|
||||
for (const pageId in pages) {
|
||||
if (pages[pageId].thumbnail) {
|
||||
thumbnails[pageId] = pages[pageId].thumbnail.source;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const results: SearchResult[] = searchResults.map((item: {
|
||||
pageid: number;
|
||||
title: string;
|
||||
snippet: string;
|
||||
}) => ({
|
||||
title: item.title,
|
||||
description: item.snippet.replace(/<[^>]*>/g, ''), // Strip HTML tags from snippet
|
||||
thumbnail: thumbnails[item.pageid.toString()],
|
||||
}));
|
||||
|
||||
// Log the search
|
||||
try {
|
||||
await prisma.search.create({
|
||||
data: {
|
||||
query,
|
||||
},
|
||||
});
|
||||
} catch (error) {
|
||||
console.error('Error logging search:', error);
|
||||
// Don't fail the search if logging fails
|
||||
}
|
||||
|
||||
return NextResponse.json({ results });
|
||||
} catch (error) {
|
||||
console.error('Error searching Wikipedia:', error);
|
||||
return NextResponse.json(
|
||||
{ error: 'Failed to search Wikipedia' },
|
||||
{ status: 500 }
|
||||
);
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,42 @@
|
||||
import { prisma } from '@/lib/db';
|
||||
import { NextResponse } from 'next/server';
|
||||
|
||||
export async function GET() {
|
||||
try {
|
||||
const today = new Date();
|
||||
today.setHours(0, 0, 0, 0);
|
||||
|
||||
const [totalArticles, searchesToday, allArticles] = await Promise.all([
|
||||
prisma.article.count(),
|
||||
prisma.search.count({
|
||||
where: {
|
||||
createdAt: {
|
||||
gte: today,
|
||||
},
|
||||
},
|
||||
}),
|
||||
prisma.article.findMany({
|
||||
select: {
|
||||
content: true,
|
||||
},
|
||||
}),
|
||||
]);
|
||||
|
||||
const totalWords = allArticles.reduce((sum, article) => {
|
||||
const words = article.content.split(/\s+/).filter(word => word.length > 0).length;
|
||||
return sum + words;
|
||||
}, 0);
|
||||
|
||||
return NextResponse.json({
|
||||
totalArticles,
|
||||
searchesToday,
|
||||
totalWords,
|
||||
});
|
||||
} catch (error) {
|
||||
console.error('Error fetching stats:', error);
|
||||
return NextResponse.json(
|
||||
{ error: 'Failed to fetch statistics' },
|
||||
{ status: 500 }
|
||||
);
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user