initial commit: rocket.new export of broadcastbeat

src/app/api/ai/article-suggestions/route.ts

@@ -0,0 +1,80 @@
+import { NextRequest, NextResponse } from 'next/server';
+import { hybridAI } from '@/lib/ai/hybridRouter';
+import { sampleArticles } from '@/lib/articles/sampleArticles';
+
+export async function POST(request: NextRequest) {
+  try {
+    const { interests, readingHistory } = await request.json();
+
+    // Build a compact article index for the AI to reason over
+    const articleIndex = sampleArticles
+      .filter((a) => a.section === 'news')
+      .map((a) => ({
+        slug: a.slug,
+        title: a.title,
+        excerpt: a.excerpt,
+        tags: a.tags,
+        category: a.category,
+        date: a.date,
+      }));
+
+    const systemPrompt = `You are a personalized content recommendation engine for BroadcastBeat, a broadcast engineering news platform.
+Given a reader's topic interests and reading history, select the 4 most relevant articles from the provided article list.
+Return ONLY a valid JSON array of slugs in order of relevance. Example: ["slug-1","slug-2","slug-3","slug-4"]
+Do not include any explanation or markdown — only the raw JSON array.`;
+
+    const userPrompt = `Reader interests: ${interests?.length ? interests.join(', ') : 'general broadcast engineering'}
+Reading history (recently read slugs): ${readingHistory?.length ? readingHistory.join(', ') : 'none'}
+
+Available articles:
+${JSON.stringify(articleIndex, null, 2)}
+
+Return the 4 most relevant article slugs as a JSON array.`;
+
+    const result = await hybridAI(
+      [
+        { role: 'system', content: systemPrompt },
+        { role: 'user', content: userPrompt },
+      ],
+      {
+        maxTokens: 200,
+        temperature: 0.3,
+        priority: 4,
+      }
+    );
+
+    const content = result.text;
+
+    let slugs: string[] = [];
+    try {
+      // Extract JSON array from response (model may wrap it in text)
+      const match = content.match(/\[[\s\S]*?\]/);
+      slugs = match ? JSON.parse(match[0]) : JSON.parse(content.trim());
+    } catch {
+      // Fallback: extract slugs with regex
+      const matches = content.match(/"([^"]+)"/g);
+      slugs = matches ? matches.map((m: string) => m.replace(/"/g, '')).slice(0, 4) : [];
+    }
+
+    // Resolve full article objects
+    const suggested = slugs
+      .map((slug: string) => sampleArticles.find((a) => a.slug === slug))
+      .filter(Boolean)
+      .slice(0, 4);
+
+    // Fallback: return latest news if AI returned nothing useful
+    if (suggested.length === 0) {
+      const fallback = sampleArticles
+        .filter((a) => a.section === 'news')
+        .slice(0, 4);
+      return NextResponse.json({ suggestions: fallback });
+    }
+
+    return NextResponse.json({ suggestions: suggested });
+  } catch (error) {
+    console.error('Article suggestions error:', error);
+    // Graceful fallback
+    const fallback = sampleArticles.filter((a) => a.section === 'news').slice(0, 4);
+    return NextResponse.json({ suggestions: fallback });
+  }
+}