wacrm/src/lib/rate-limit.ts
Arnas Donauskas b0194dfc27 feat(ai): polish auto-reply — inbox controls, real handoff, usage logging
Makes the AI auto-reply bot visible and controllable from the inbox,
completes the handoff, and records token spend. Builds on the existing
lib/ai engine rather than replacing it.

Track A — user-facing
- messages.ai_generated flag → small "AI" badge on bot-generated bubbles
- "Take over" / "Resume AI" banner per conversation
  (POST /api/ai/autoreply/[id]) — take-over pauses + assigns to the agent
- handoff now assigns to a configurable target (agent or unassigned
  queue) and writes an internal note summarizing the exchange; the
  existing on_conversation_assigned trigger notifies the assignee
- Settings → AI: "Hand off to" target picker

Track B — observability + safety
- providers return normalized token usage; logged per run to ai_usage_log
  (admin-readable) from both auto-reply and draft
- account-wide auto-reply rate limit (30/min) on top of the
  per-conversation cap

Migration: 033_ai_reply_polish.sql (messages.ai_generated,
ai_configs.handoff_agent_id, conversations.ai_handoff_summary,
ai_usage_log). Tests + typecheck + lint pass (607 tests).

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-08 14:03:33 +03:00

178 lines
6.7 KiB
TypeScript

/**
* In-memory per-key rate limiter.
*
* Fixed-window counter (not token bucket): every identifier gets a
* fresh N-request budget each window. Simple, allocation-light, and
* fine for a single-instance VPS — which is how forkers of this
* template will usually deploy.
*
* Trade-off: a single Node process holds the Map, so horizontal scale
* (multiple regions, multiple Hostinger nodes, Vercel serverless fan-
* out) silently defeats the limit. If you scale beyond one instance,
* swap the `check` implementation for Redis / Upstash / Cloudflare
* Durable Objects keeping the same return shape. The call sites won't
* change.
*
* Memory: entries are ~50 bytes each. With LIGHT_SWEEP below, expired
* keys get cleared opportunistically on every ~1 000th call, so a
* healthy instance stays in the low-MB range even with thousands of
* distinct users. No background timer — works in serverless edge
* runtimes that don't keep timers alive across requests.
*/
import { NextResponse } from 'next/server';
export interface RateLimitOptions {
/** Max requests allowed in `windowMs`. */
limit: number;
/** Window size, milliseconds. */
windowMs: number;
}
export interface RateLimitResult {
success: boolean;
/** Requests still allowed in the current window. */
remaining: number;
/** Unix ms when the bucket refills. */
reset: number;
limit: number;
}
interface Entry {
count: number;
resetAt: number;
}
const buckets = new Map<string, Entry>();
// Opportunistic cleanup. Running a sweep on every call would be
// quadratic; running it 1-in-N lets the Map self-drain without a
// background timer.
const LIGHT_SWEEP_EVERY = 1000;
let callsSinceSweep = 0;
function sweepExpired(now: number) {
for (const [k, v] of buckets) {
if (v.resetAt <= now) buckets.delete(k);
}
}
export function checkRateLimit(
key: string,
{ limit, windowMs }: RateLimitOptions,
): RateLimitResult {
const now = Date.now();
callsSinceSweep += 1;
if (callsSinceSweep >= LIGHT_SWEEP_EVERY) {
callsSinceSweep = 0;
sweepExpired(now);
}
const entry = buckets.get(key);
if (!entry || entry.resetAt <= now) {
buckets.set(key, { count: 1, resetAt: now + windowMs });
return { success: true, remaining: limit - 1, reset: now + windowMs, limit };
}
if (entry.count >= limit) {
return { success: false, remaining: 0, reset: entry.resetAt, limit };
}
entry.count += 1;
return {
success: true,
remaining: limit - entry.count,
reset: entry.resetAt,
limit,
};
}
/**
* Standard 429 response with the headers clients expect (RFC 6585 +
* draft-ietf-httpapi-ratelimit-headers). Callers just `return` this.
*/
export function rateLimitResponse(result: RateLimitResult): NextResponse {
const retryAfterSec = Math.max(1, Math.ceil((result.reset - Date.now()) / 1000));
return NextResponse.json(
{
error: 'Rate limit exceeded',
retry_after_seconds: retryAfterSec,
},
{
status: 429,
headers: {
'Retry-After': String(retryAfterSec),
'X-RateLimit-Limit': String(result.limit),
'X-RateLimit-Remaining': String(result.remaining),
'X-RateLimit-Reset': String(Math.ceil(result.reset / 1000)),
},
},
);
}
/** Preconfigured budgets, tweak here not at call sites. */
export const RATE_LIMITS = {
/** Individual message send. 60/min per user = one per second
* sustained, comfortable for a live human typing. */
send: { limit: 60, windowMs: 60_000 },
/** Broadcast dispatch. 5/min per user — even a 1 000-recipient
* broadcast is one call; this caps the rate at which a single user
* can launch campaigns, not the messages inside one. */
broadcast: { limit: 5, windowMs: 60_000 },
/** Reaction add/swap/remove. More permissive than send — users
* fidget with reactions and a single "swap" is actually two calls
* (remove + add) under the hood. */
react: { limit: 120, windowMs: 60_000 },
/** Invitation peek (public, per-IP). 30/min lets a forwarded link
* retry a handful of times under flaky connectivity without
* enabling brute-force token enumeration. With 256-bit tokens the
* enumeration risk is theoretical; this is belt-and-braces. */
invitationPeek: { limit: 30, windowMs: 60_000 },
/** Invitation redeem (authed, per-IP+user). Tighter than peek —
* successful redemption mutates two profiles and an invite row, so
* the abuse surface is "spam join attempts." */
invitationRedeem: { limit: 10, windowMs: 60_000 },
/** Admin-only account / member-management actions: create/revoke
* invitation, rename account, change member role, remove member,
* transfer ownership. 30/min per user is comfortably above any
* realistic legitimate use (the Members tab is a clicks-only UI)
* while still bounding accidental abuse from a script run in a
* loop or a compromised admin session spamming role flips. */
adminAction: { limit: 30, windowMs: 60_000 },
/** Public REST API (`/api/v1/*`), keyed per API key. 120/min ≈ 2
* req/s sustained — comfortable for a polling integration or an
* automation firing on inbound events, while bounding a runaway
* script. Like every bucket here it's per-process; a multi-
* instance deploy needs the Redis swap described at the top of
* this file (the per-key call sites don't change). */
publicApi: { limit: 120, windowMs: 60_000 },
/** AI draft-reply generation, per user. 20/min is generous for an
* agent clicking "Draft with AI" while working a thread, and bounds
* spend on the account's own LLM key against an accidental
* hold-down / script. */
aiDraft: { limit: 20, windowMs: 60_000 },
/** AI draft-reply generation, per account. Caps the WHOLE team's
* draws on the one shared BYO provider key — without this, N agents
* each under their per-user limit could still stampede the account's
* key past the provider's own rate limit. 60/min ≈ three busy agents
* drafting flat-out. */
aiDraftAccount: { limit: 60, windowMs: 60_000 },
/** AI auto-reply generation, per account. The per-conversation cap
* (`auto_reply_max_per_conversation`) bounds one thread; this bounds
* the whole account across threads, so a burst of inbound from many
* customers at once can't run the BYO key past the provider's limit
* or the owner's budget. 30/min is generous for organic inbound while
* capping a stampede; excess inbounds simply don't get an auto-reply
* (they still land in the inbox for a human). */
aiAutoReplyAccount: { limit: 30, windowMs: 60_000 },
} as const;
/** Test-only helper. Clears the in-memory state so unit tests don't
* leak buckets across files. Not wired up in production code. */
export function __resetRateLimitForTests() {
buckets.clear();
callsSinceSweep = 0;
}