AngeloooooandDraculabo
8ed4593f73
* Refactor Gemini model display: filter old versions, group low/high pro, and improve naming * Fix potential negative minutes and refine Gemini 3 Pro grouping logic based on PR feedback * The account change process has been sped up * Address PR review: enhance error message and parameterize polling interval in process handler * Address PR review: fix potential race condition in database backup logic * fix: prevent renderer white screen and harden sentry gating * feat: localize model labels * chore: enable hoisted node-linker * chore: ignore .agent/.claude/.codex in prettier --------- Co-authored-by: Draculabo <[email protected]>
1.3 KiB
1.3 KiB
title, impact, impactDescription, tags
| title | impact | impactDescription | tags |
|---|---|---|---|
| Cross-Request LRU Caching | HIGH | caches across requests | server, cache, lru, cross-request |
Cross-Request LRU Caching
React.cache() only works within one request. For data shared across sequential requests (user clicks button A then button B), use an LRU cache.
Implementation:
import { LRUCache } from 'lru-cache';
const cache = new LRUCache<string, any>({
max: 1000,
ttl: 5 * 60 * 1000, // 5 minutes
});
export async function getUser(id: string) {
const cached = cache.get(id);
if (cached) return cached;
const user = await db.user.findUnique({ where: { id } });
cache.set(id, user);
return user;
}
// Request 1: DB query, result cached
// Request 2: cache hit, no DB query
Use when sequential user actions hit multiple endpoints needing the same data within seconds.
With Vercel's Fluid Compute: LRU caching is especially effective because multiple concurrent requests can share the same function instance and cache. This means the cache persists across requests without needing external storage like Redis.
In traditional serverless: Each invocation runs in isolation, so consider Redis for cross-process caching.
Reference: https://github.com/isaacs/node-lru-cache