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fix(moderation): remove manual badword list and fix deferral regex false positives

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- Remove LOCAL_BADWORDS array (25 hardcoded words) and FALSE_POSITIVE_WHITELISTS
- Remove detectLocalBadwords function — all detection now goes through API pipeline
- Fix DEFERRAL_ANALYSIS_PATTERN: remove overly broad patterns (admin perlu, bisa berpotensi, maaf/sorry, saya tidak yakin)
- Expand DEFERRAL_EXCEPTION_PATTERN to catch more decisive-deferral variations
- Update tests to reflect API-only detection (local fallback removed)

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
MythEclipse
2026-06-01 19:00:16 +07:00
co-authored by Claude Opus 4.8
parent a643125c7b
commit 13efb576d6
3 changed files with 36 additions and 108 deletions
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src/moderation/indonesianTextNormalizer.ts
+16 -101
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@@ -118,84 +118,9 @@ export function normalizeDiscordCustomEmoji(text: string): {
return { text: normalized, emojiNames };
}
// ---------------------------------------------------------------------------
// Local fallback badword list (used when NVIDIA API is unavailable)
// ---------------------------------------------------------------------------
const LOCAL_BADWORDS = [
"anjing",
"bangsat",
"brengsek",
"bajingan",
"kontol",
"memek",
"tai",
"goblok",
"tolol",
"bego",
"sialan",
"jancuk",
"kampret",
"pepek",
"jembut",
"ngentot",
"ngewe",
"coli",
"celaka",
"laknat",
"pantek",
"entod",
"ndasmu",
"ndas",
"piyo",
"asu",
];
const FALSE_POSITIVE_WHITELISTS: Record<string, string[]> = {
asu: [
"asus",
"masuk",
"termasuk",
"dimasukkan",
"memasukkan",
"kasur",
"asumsi",
"asuransi",
"asupan",
"pasukan",
"pasundan",
],
goblok: ["goblok"],
kontol: ["kontol"],
memek: ["memek"],
tolol: ["tolol"],
};
function detectLocalBadwords(text: string): string[] {
const lowerText = text.toLowerCase();
const words = lowerText.match(/[\p{L}\p{N}_]+/gu) || [];
const isRealHit = (hit: string, whitelist: string[]): boolean => {
for (const w of words) {
if (w.includes(hit)) {
if (w === hit) return true;
if (!whitelist.includes(w)) return true;
}
}
return false;
};
const hits: string[] = [];
for (const badword of LOCAL_BADWORDS) {
const whitelist = FALSE_POSITIVE_WHITELISTS[badword] ?? [badword];
if (isRealHit(badword, whitelist)) {
hits.push(badword);
}
}
return Array.from(new Set(hits));
}
// Local badword detection removed (lines 121-198).
// All detection now goes through the API pipeline (NVIDIA → Primary AI → Groq)
// to eliminate false positives from substring matching and hardcoded whitelists.
function normalizeBadwordCacheKey(text: string): string {
return text.trim().replace(/\s+/g, " ").toLowerCase();
@@ -496,15 +421,18 @@ async function callNemotronContentSafety(text: string): Promise<string[]> {
// ---------------------------------------------------------------------------
/**
* Detect badwords in text using a **three-tier cache strategy**:
* Detect badwords in text using a **two-tier cache + API pipeline**:
*
* 1. **In-memory cache** (BADWORD_CACHE_TTL_MS, 10 min) — fastest path,
* keyed by the full normalized text string.
* 2. **DB cache** (DB_CACHE_TTL_MS, 24 h) — same full-text key, persisted
* across restarts. Uses the FULL normalized text (not per-word) because
* context matters: "kau" alone is clean, but "awas kau" can be a threat.
* 3. **API/fallback pipeline** (NVIDIA → Primary AI → Groq → local lexical)
* 3. **API pipeline** (NVIDIA → Primary AI → Groq)
* only runs when both cache layers miss.
*
* No local hardcoded badword list — all detection goes through AI APIs
* to eliminate false positives from substring matching.
*/
export async function detectIndonesianBadwords(
text: string,
@@ -532,25 +460,12 @@ export async function detectIndonesianBadwords(
return flags;
}
// ── Tier 3: API / fallback pipeline ──
// 3a. Local lexical check (instant, no network)
const localHits = detectLocalBadwords(text);
if (localHits.length > 0) {
setCachedBadwords(cacheKey, localHits);
await upsertCachedText(
cacheKey,
localHits,
"local",
Date.now() + DB_CACHE_TTL_MS,
);
return localHits;
}
// ── Tier 3: API pipeline ──
const hits = new Set<string>();
let sourceUsed: "local" | "nvidia" | "primary_ai" | "groq" = "local";
let sourceUsed: "nvidia" | "primary_ai" | "groq" = "primary_ai";
// 3b. Try NVIDIA API if key is configured and not rate limited.
// 3a. Try NVIDIA API if key is configured and not rate limited.
const apiKey = config.NVIDIA_NEMOTRON_API_KEY;
if (apiKey && Date.now() >= nemotronUnavailableUntil) {
try {
@@ -569,12 +484,12 @@ export async function detectIndonesianBadwords(
}
log.warn(
{ error },
"NVIDIA Nemotron API call failed, falling back to primary AI then local detection",
"NVIDIA Nemotron API call failed, falling back to primary AI",
);
}
}
// 3c. Try the main AI model next.
// 3b. Try the main AI model next.
if (hits.size === 0 && Date.now() >= primaryAiUnavailableUntil) {
try {
const primaryHits = await callPrimaryAiModeration(text);
@@ -592,12 +507,12 @@ export async function detectIndonesianBadwords(
}
log.warn(
{ error },
"Primary AI badword detection failed, falling back to Groq then local detection",
"Primary AI badword detection failed, falling back to Groq",
);
}
}
// 3d. Try Groq Llama Prompt Guard as final API fallback.
// 3c. Try Groq Llama Prompt Guard as final API fallback.
if (hits.size === 0 && Date.now() >= groqUnavailableUntil) {
const groqKey = config.GROQ_API_KEY;
if (groqKey) {
@@ -616,7 +531,7 @@ export async function detectIndonesianBadwords(
}
log.warn(
{ error },
"Groq Llama Prompt Guard moderation failed, falling back to local detection",
"Groq Llama Prompt Guard moderation failed",
);
}
}