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Adds three WhatsApp-standard affordances to the inbox: per-message emoji reactions, reply-with-quote, and copy-text. Bubbles stay pure presenters — actions layer on by composition (MessageActions wraps MessageBubble). Hover toolbar on desktop, long-press (onContextMenu) on touch. Data model (migration 009): - messages.reply_to_message_id (self-FK, ON DELETE SET NULL) so replies survive a deleted parent - message_reactions table — one row per (message, actor) with a unique constraint, conversation_id denormalised so Supabase Realtime can filter without a join - RLS scoped via conversation ownership; service-role bypass for the webhook API: - /api/whatsapp/send accepts reply_to_message_id, resolves the parent's Meta message_id and forwards it as context.message_id - /api/whatsapp/react (new) sends Meta reaction payloads and mirrors the upsert/delete into message_reactions - Webhook stops storing inbound reactions as fake text messages and instead upserts/deletes message_reactions; inbound replies (context.id) resolve to internal UUID and populate reply_to_message_id UI: - MessageActions hover toolbar with inline 6-emoji Popover (static set; no emoji-picker library) - ReplyQuote shared between the in-bubble quote and the composer chip - MessageReactions pill row with click-to-toggle - Thread subscribes to message_reactions filtered by conversation_id; optimistic upsert with rollback on failure Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
136 lines
4.1 KiB
TypeScript
136 lines
4.1 KiB
TypeScript
/**
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* In-memory per-key rate limiter.
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*
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* Fixed-window counter (not token bucket): every identifier gets a
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* fresh N-request budget each window. Simple, allocation-light, and
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* fine for a single-instance VPS — which is how forkers of this
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* template will usually deploy.
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*
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* Trade-off: a single Node process holds the Map, so horizontal scale
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* (multiple regions, multiple Hostinger nodes, Vercel serverless fan-
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* out) silently defeats the limit. If you scale beyond one instance,
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* swap the `check` implementation for Redis / Upstash / Cloudflare
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* Durable Objects keeping the same return shape. The call sites won't
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* change.
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*
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* Memory: entries are ~50 bytes each. With LIGHT_SWEEP below, expired
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* keys get cleared opportunistically on every ~1 000th call, so a
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* healthy instance stays in the low-MB range even with thousands of
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* distinct users. No background timer — works in serverless edge
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* runtimes that don't keep timers alive across requests.
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*/
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import { NextResponse } from 'next/server';
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export interface RateLimitOptions {
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/** Max requests allowed in `windowMs`. */
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limit: number;
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/** Window size, milliseconds. */
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windowMs: number;
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}
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export interface RateLimitResult {
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success: boolean;
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/** Requests still allowed in the current window. */
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remaining: number;
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/** Unix ms when the bucket refills. */
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reset: number;
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limit: number;
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}
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interface Entry {
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count: number;
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resetAt: number;
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}
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const buckets = new Map<string, Entry>();
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// Opportunistic cleanup. Running a sweep on every call would be
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// quadratic; running it 1-in-N lets the Map self-drain without a
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// background timer.
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const LIGHT_SWEEP_EVERY = 1000;
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let callsSinceSweep = 0;
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function sweepExpired(now: number) {
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for (const [k, v] of buckets) {
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if (v.resetAt <= now) buckets.delete(k);
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}
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}
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export function checkRateLimit(
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key: string,
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{ limit, windowMs }: RateLimitOptions,
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): RateLimitResult {
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const now = Date.now();
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callsSinceSweep += 1;
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if (callsSinceSweep >= LIGHT_SWEEP_EVERY) {
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callsSinceSweep = 0;
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sweepExpired(now);
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}
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const entry = buckets.get(key);
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if (!entry || entry.resetAt <= now) {
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buckets.set(key, { count: 1, resetAt: now + windowMs });
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return { success: true, remaining: limit - 1, reset: now + windowMs, limit };
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}
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if (entry.count >= limit) {
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return { success: false, remaining: 0, reset: entry.resetAt, limit };
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}
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entry.count += 1;
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return {
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success: true,
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remaining: limit - entry.count,
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reset: entry.resetAt,
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limit,
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};
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}
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/**
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* Standard 429 response with the headers clients expect (RFC 6585 +
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* draft-ietf-httpapi-ratelimit-headers). Callers just `return` this.
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*/
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export function rateLimitResponse(result: RateLimitResult): NextResponse {
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const retryAfterSec = Math.max(1, Math.ceil((result.reset - Date.now()) / 1000));
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return NextResponse.json(
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{
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error: 'Rate limit exceeded',
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retry_after_seconds: retryAfterSec,
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},
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{
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status: 429,
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headers: {
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'Retry-After': String(retryAfterSec),
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'X-RateLimit-Limit': String(result.limit),
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'X-RateLimit-Remaining': String(result.remaining),
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'X-RateLimit-Reset': String(Math.ceil(result.reset / 1000)),
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},
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},
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);
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}
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/** Preconfigured budgets, tweak here not at call sites. */
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export const RATE_LIMITS = {
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/** Individual message send. 60/min per user = one per second
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* sustained, comfortable for a live human typing. */
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send: { limit: 60, windowMs: 60_000 },
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/** Broadcast dispatch. 5/min per user — even a 1 000-recipient
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* broadcast is one call; this caps the rate at which a single user
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* can launch campaigns, not the messages inside one. */
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broadcast: { limit: 5, windowMs: 60_000 },
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/** Reaction add/swap/remove. More permissive than send — users
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* fidget with reactions and a single "swap" is actually two calls
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* (remove + add) under the hood. */
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react: { limit: 120, windowMs: 60_000 },
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} as const;
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/** Test-only helper. Clears the in-memory state so unit tests don't
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* leak buckets across files. Not wired up in production code. */
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export function __resetRateLimitForTests() {
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buckets.clear();
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callsSinceSweep = 0;
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}
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