- Surface AI review scores across skill pages, browse, and search - Add dedicated /reviewed page with score filtering - Add recommended sort using Meilisearch relevance + AI scores - Fix search sort defaulting to stars instead of recommended - Fix CLI TypeScript null check for aiScore in search command - Adjust cache TTL for reviewed content Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
91 lines
2.8 KiB
TypeScript
91 lines
2.8 KiB
TypeScript
import { NextResponse, type NextRequest } from 'next/server';
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import { createDb, skillQueries, type skills } from '@skillhub/db';
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import { getCached, setCache, cacheKeys, cacheTTL } from '@/lib/cache';
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import { withRateLimit, createRateLimitResponse, createRateLimitHeaders } from '@/lib/rate-limit';
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const db = createDb();
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type Skill = typeof skills.$inferSelect;
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interface SkillData {
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id: string;
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name: string;
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description: string | null;
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githubOwner: string;
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githubRepo: string;
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githubStars: number | null;
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downloadCount: number | null;
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securityStatus: string | null;
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isVerified: boolean | null;
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compatibility: unknown;
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}
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interface FeaturedResponse {
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skills: SkillData[];
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}
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export async function GET(request: NextRequest) {
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// Rate limiting
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const rateLimitResult = await withRateLimit(request, 'anonymous');
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if (!rateLimitResult.allowed) {
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return createRateLimitResponse(rateLimitResult);
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}
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try {
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const searchParams = request.nextUrl.searchParams;
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const limit = parseInt(searchParams.get('limit') || '6');
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// Try to get from cache first (only for default limit)
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const cacheKey = cacheKeys.featuredSkills();
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if (limit === 6) {
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const cached = await getCached<FeaturedResponse>(cacheKey);
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if (cached) {
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return NextResponse.json(cached, {
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headers: { 'X-Cache': 'HIT', ...createRateLimitHeaders(rateLimitResult) },
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});
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}
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}
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// Get featured skills, fallback to popularity-based ranking
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// Uses adaptive algorithm: quality + freshness + engagement
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let featuredSkills = await skillQueries.getFeatured(db, limit);
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// If no manually featured skills, use adaptive popularity with owner/repo diversity
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if (featuredSkills.length === 0) {
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featuredSkills = await skillQueries.getFeaturedWithDiversity(db, limit, 2, 3);
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}
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const data: FeaturedResponse = {
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skills: featuredSkills.map((skill: Skill) => ({
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id: skill.id,
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name: skill.name,
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description: skill.description,
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githubOwner: skill.githubOwner,
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githubRepo: skill.githubRepo,
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githubStars: skill.githubStars,
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downloadCount: skill.downloadCount,
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securityStatus: skill.securityStatus,
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isVerified: skill.isVerified,
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compatibility: skill.compatibility,
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reviewStatus: skill.reviewStatus,
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aiScore: skill.latestAiScore,
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})),
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};
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// Cache the result (2 hours)
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if (limit === 6) {
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await setCache(cacheKey, data, cacheTTL.featured);
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}
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return NextResponse.json(data, {
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headers: { 'X-Cache': 'MISS', ...createRateLimitHeaders(rateLimitResult) },
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});
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} catch (error) {
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console.error('Error fetching featured skills:', error);
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return NextResponse.json(
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{ error: 'Failed to fetch featured skills' },
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{ status: 500 }
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);
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}
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}
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