refactor: split llmModerationClient.ts + add tests + metrics
## Split llmModerationClient.ts (2103 → 3 files) - **moderationBuilders.ts** (67 lines) — shared: escapeXml, getAnalysisContent, buildReferenceXml - **mediaAnalysisClient.ts** (656 lines) — vision analysis with multi-layer LRU/DB/phash caching, image/video download, ffmpeg frame extraction, prepareMediaMessage - **moderationOrchestrator.ts** (998 lines) — callModerationLLM, runTextOnlyBatch, runMediaBatch, runModerationAnalysis, runSimpleTextFallback - **llmModerationClient.ts** (30 lines) — re-export bridge (backward compat) No import changes needed — aiAnalysisWorker.ts still imports from llmModerationClient.js. ## Unit tests (backend) - vitest.config.ts + e2e.test.ts with 9 tests against production: - health, metrics, dashboard/stats, recordings, config, auth, guilds, negative (404/400) ## Monitoring metrics - moderationMetrics.ts in backend health module: - LLM call count/duration/tokens - Cache hit/miss per layer - Media analysis count/download duration - Batch size distribution, errors, SearXNG, auto-delete
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/**
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* mediaAnalysisClient.ts
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*
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* Handles: vision analysis with multi-layer LRU/DB/phash caching,
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* image/video download, ffmpeg frame extraction, and media message
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* preparation for the LLM moderation pipeline.
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*/
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import { execFile } from "node:child_process";
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import { createChildLogger } from "@bete/shared/logger";
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import { readFile, writeFile, unlink, rm, mkdtemp } from "node:fs/promises";
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import { tmpdir } from "node:os";
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import path from "node:path";
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import { promisify } from "node:util";
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import { delay } from "@bete/shared/utils";
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import { LRUCache } from "lru-cache";
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import { config } from "../../shared/config/config.js";
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import { resizeImageForVision } from "../attachment-upload/imageResizer.js";
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import { extractMessageMediaEvidence } from "../message-capture/messageMetadata.js";
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import type {
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AttachmentRecord,
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MessageRecord,
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} from "../message-capture/types.js";
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import { llmVision } from "./llmClient.js";
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import { sanitizeAiContent } from "./moderationPrompt.js";
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import {
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buildCustomEmojiVisionPrompt,
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buildGeneralImageVisionPrompt,
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buildStickerTextOnlyWarning,
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buildStickerVisionPrompt,
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} from "./stickerPrompt.js";
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import {
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acquireMediaAnalysisLock,
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computeImagePhash,
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deleteCachedMediaAnalysis,
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getCachedMediaAnalysis,
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getCachedMediaByPhash,
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makeCustomEmojiCacheKey,
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makeImageCacheKey,
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makeStickerCacheKey,
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upsertCachedMediaAnalysis,
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upsertCachedMediaByPhash,
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} from "./textCacheStore.js";
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import { sniffImageMimeType } from "./imageMimeSniffer.js";
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import { fetchUrlSafely, extractUrlsFromText } from "./urlFetcher.js";
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import {
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getStickerFromCache,
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isStickerCacheReady,
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uploadAndCacheSticker,
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} from "./stickerCache.js";
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import { searchSearxng, extractSearchQueries, formatSearchResults } from "./searxngSearch.js";
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import { getUserProfile } from "./userProfileStore.js";
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import { initializeUserReputation } from "./userReputationStore.js";
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import { escapeXml, getAnalysisContent, buildReferenceXml } from "./moderationBuilders.js";
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// ---------------------------------------------------------------------------
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// Types
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// ---------------------------------------------------------------------------
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export type MessageImagePart = {
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type: "image_url";
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image_url: { url: string };
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sourceLabel: string;
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stickerName?: string;
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customEmojiId?: string;
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customEmojiName?: string;
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};
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export interface PreparedMediaMessage {
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targetId: string;
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messageBlock: string;
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}
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interface MediaCandidate {
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messageId: string;
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url: string;
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label: string;
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stickerName?: string;
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customEmojiId?: string;
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customEmojiName?: string;
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}
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// ---------------------------------------------------------------------------
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// Caches
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// ---------------------------------------------------------------------------
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const visionLruCache = new LRUCache<string, string>({
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max: 500,
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ttl: 24 * 60 * 60 * 1000,
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});
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const inFlightVisionCalls = new Map<string, Promise<string>>();
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const FAILED_ANALYSIS_PREFIX =
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"GAGAL DIANALISIS — gambar tidak dapat diunduh atau vision API gagal setelah 3x percobaan. JANGAN mengasumsikan gambar aman hanya karena gagal dianalisis. Gunakan metadata URL/nama file saja sebagai petunjuk.";
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// ---------------------------------------------------------------------------
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// Image helpers
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// ---------------------------------------------------------------------------
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function addImageToMap(
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imageMap: Map<string, MessageImagePart[]>,
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targetId: string,
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part: MessageImagePart,
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): void {
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const existing = imageMap.get(targetId) ?? [];
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if (existing.length < 8) {
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existing.push(part);
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imageMap.set(targetId, existing);
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}
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}
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function buildMediaCandidates(
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messageId: string,
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evidence: ReturnType<typeof extractMessageMediaEvidence>,
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): MediaCandidate[] {
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return [
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...evidence.stickers
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.filter((s) => s.url)
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.map(
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(s): MediaCandidate => ({
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messageId,
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url: s.url,
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label: `[gambar di atas adalah sticker "${s.name}" dari pesan id=${messageId}]`,
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stickerName: s.name,
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}),
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),
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...evidence.embeds.flatMap((embed): MediaCandidate[] =>
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[
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embed.image
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? ({ messageId, url: embed.image, label: `[gambar di atas berasal dari embed image pada pesan id=${messageId}]` } as MediaCandidate)
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: null,
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embed.thumbnail
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? ({ messageId, url: embed.thumbnail, label: `[gambar di atas berasal dari embed thumbnail pada pesan id=${messageId}]` } as MediaCandidate)
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: null,
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].filter((c): c is MediaCandidate => c !== null),
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),
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...evidence.customEmojis.map(
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(emoji): MediaCandidate => ({
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messageId,
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url: emoji.url,
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label: `[gambar di atas adalah custom emoji "${emoji.name}" dari pesan id=${messageId}]`,
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customEmojiId: emoji.id,
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customEmojiName: emoji.name,
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}),
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),
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];
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}
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// ---------------------------------------------------------------------------
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// Media detection
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// ---------------------------------------------------------------------------
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export function hasMediaContent(
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target: MessageRecord,
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attachments?: AttachmentRecord[],
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): boolean {
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if (target.metadata) {
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const evidence = extractMessageMediaEvidence(target.metadata);
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if (
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evidence.stickers.length > 0 ||
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evidence.embeds.length > 0 ||
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evidence.attachments.length > 0
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)
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return true;
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}
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if (attachments?.some((a) => a.message_id === target.id)) return true;
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return false;
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}
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// ---------------------------------------------------------------------------
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// Single-image vision analysis
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// ---------------------------------------------------------------------------
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export const analyzeSingleMediaImage = async (
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messageId: string,
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image: MessageImagePart,
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): Promise<string> => {
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const cacheKey = image.customEmojiId
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? makeCustomEmojiCacheKey(image.customEmojiId)
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: image.stickerName
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? makeStickerCacheKey(image.stickerName)
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: makeImageCacheKey(image.image_url.url);
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const log = createChildLogger("mediaAnalysis");
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// Layer 0: LRU
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const lruCached = visionLruCache.get(cacheKey);
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if (lruCached) {
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log.debug({ cacheKey }, "Vision LRU cache HIT (in-memory)");
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return `[Media analysis for message ${messageId}] ${image.sourceLabel}: ${lruCached}`;
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}
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// Layer 1: DB
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const cached = await getCachedMediaAnalysis(cacheKey);
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if (cached) {
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visionLruCache.set(cacheKey, cached);
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log.debug({ cacheKey }, "Media analysis cache HIT (DB → LRU)");
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return `[Media analysis for message ${messageId}] ${image.sourceLabel}: ${cached}`;
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}
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// In-flight dedupe
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const existing = inFlightVisionCalls.get(cacheKey);
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if (existing) {
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log.debug({ cacheKey }, "Media analysis in-flight dedupe");
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const result = await existing;
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return `[Media analysis for message ${messageId}] ${image.sourceLabel}: ${result}`;
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}
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const promptText = image.stickerName
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? buildStickerVisionPrompt(image.stickerName, messageId)
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: image.customEmojiName
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? buildCustomEmojiVisionPrompt(image.customEmojiName, messageId)
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: buildGeneralImageVisionPrompt(image.sourceLabel, messageId);
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const visionPromise = (async (): Promise<string> => {
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// Distributed lock
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const locked = await acquireMediaAnalysisLock(cacheKey, Date.now() + 60000);
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if (!locked) {
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log.debug({ cacheKey }, "Distributed lock — polling");
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for (let i = 0; i < 15; i++) {
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await new Promise((r) => setTimeout(r, 2000));
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const polled = await getCachedMediaAnalysis(cacheKey);
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if (polled) {
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visionLruCache.set(cacheKey, polled);
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return polled;
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}
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}
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log.warn({ cacheKey }, "Distributed lock polling timed out");
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return FAILED_ANALYSIS_PREFIX;
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}
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// phash check
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let phash: string | null = null;
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if (image.image_url.url.startsWith("data:")) {
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try {
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const base64Data = image.image_url.url.split(",")[1];
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if (base64Data) {
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const imgBuffer = Buffer.from(base64Data, "base64");
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phash = await computeImagePhash(imgBuffer);
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if (phash) {
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const phashCached = await getCachedMediaByPhash(phash);
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if (phashCached) {
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visionLruCache.set(cacheKey, phashCached);
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await upsertCachedMediaAnalysis(cacheKey, phashCached, "vision_llm", Date.now() + 24 * 60 * 60 * 1000).catch(() => {});
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return phashCached;
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}
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}
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}
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} catch { phash = null; }
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}
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// Vision API call
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let lastError: Error | null = null;
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for (let attempt = 0; attempt < 3; attempt++) {
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try {
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const content = await llmVision(promptText, image.image_url);
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if (content) {
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await upsertCachedMediaAnalysis(cacheKey, content, "vision_llm", Date.now() + 24 * 60 * 60 * 1000);
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visionLruCache.set(cacheKey, content);
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if (phash) {
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upsertCachedMediaByPhash(phash, content, "vision_llm", Date.now() + 7 * 24 * 60 * 60 * 1000).catch(() => {});
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}
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return content;
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}
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log.warn({ messageId }, "Vision API null response");
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break;
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} catch (err) {
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lastError = err instanceof Error ? err : new Error(String(err));
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if (attempt < 2) {
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const backoffMs = Math.min(2_000 * 3 ** attempt + Math.random() * 500, 30_000);
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log.warn({ messageId, attempt: attempt + 1, backoffMs, error: lastError.message }, "Vision retry");
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await delay(backoffMs);
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}
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}
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}
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log.warn({ messageId, lastError: lastError?.message ?? "null" }, "Vision failed after 3 attempts");
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await deleteCachedMediaAnalysis(cacheKey).catch(() => {});
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return FAILED_ANALYSIS_PREFIX;
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})();
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inFlightVisionCalls.set(cacheKey, visionPromise);
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try {
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const content = await visionPromise;
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return `[Media analysis for message ${messageId}] ${image.sourceLabel}: ${content}`;
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} catch (outerErr) {
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log.error({ messageId, cacheKey, error: outerErr instanceof Error ? outerErr.message : String(outerErr) }, "visionPromise threw unexpectedly");
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return `[Media analysis for message ${messageId}] ${image.sourceLabel}: ${FAILED_ANALYSIS_PREFIX}`;
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} finally {
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inFlightVisionCalls.delete(cacheKey);
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}
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};
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// ---------------------------------------------------------------------------
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// Download helpers
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// ---------------------------------------------------------------------------
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async function downloadSingleAttachment(
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att: AttachmentRecord,
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targetId: string,
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maxDimension: number,
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imageMap: Map<string, MessageImagePart[]>,
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): Promise<void> {
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const log = createChildLogger("mediaAnalysis");
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const urlToUse = att.uploaded_url ?? att.discord_url ?? null;
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if (!urlToUse) return;
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const controller = new AbortController();
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const timeoutId = setTimeout(() => controller.abort(), 15000);
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try {
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const res = await fetch(urlToUse, { signal: controller.signal });
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if (!res.ok || !res.body) return;
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let totalBytes = 0;
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const chunks: Uint8Array[] = [];
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const reader = res.body.getReader();
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while (true) {
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const { done, value } = await reader.read();
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if (done) break;
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if (value) {
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totalBytes += value.length;
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if (totalBytes > 10 * 1024 * 1024) { reader.cancel(); return; }
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chunks.push(value);
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}
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}
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const imageBytes = Buffer.concat(chunks);
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const sniffedMime = sniffImageMimeType(imageBytes);
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if (!sniffedMime && att.type.startsWith("video/")) {
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await extractVideoFrames(att, imageBytes, targetId, maxDimension, imageMap);
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return;
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}
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if (!sniffedMime) return;
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const { data: resizedBuffer, mimeType: resizedMime } = await resizeImageForVision(imageBytes, maxDimension);
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const dataUrl = `data:${resizedMime};base64,${resizedBuffer.toString("base64")}`;
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addImageToMap(imageMap, targetId, {
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type: "image_url",
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image_url: { url: dataUrl },
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sourceLabel: `[gambar di atas adalah attachment ${att.filename} dari pesan id=${att.message_id}]`,
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});
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} catch (err) {
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log.warn({ attachmentId: att.id, error: err instanceof Error ? err.message : String(err) }, "Download failed");
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} finally {
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clearTimeout(timeoutId);
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}
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}
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async function extractVideoFrames(
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att: AttachmentRecord,
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videoBytes: Buffer,
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targetId: string,
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maxDimension: number,
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imageMap: Map<string, MessageImagePart[]>,
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): Promise<void> {
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const log = createChildLogger("mediaAnalysis");
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const execFileAsync = promisify(execFile);
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const tmpDir = await mkdtemp(path.join(tmpdir(), "bete-video-"));
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const inputPath = path.join(tmpDir, att.filename || "video.mp4");
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const outputPattern = path.join(tmpDir, "frame-%03d.jpg");
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try {
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await writeFile(inputPath, videoBytes);
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const { stdout: durationStr } = await execFileAsync("/usr/bin/ffprobe", [
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"-v", "error", "-show_entries", "format=duration", "-of", "csv=p=0", inputPath,
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], { timeout: 10000 });
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const duration = parseFloat(durationStr.trim()) || 1;
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const fps = (3 / duration).toFixed(6);
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await execFileAsync("/usr/bin/ffmpeg", [
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"-i", inputPath, "-vf", `fps=${fps}`, "-frames:v", "4", "-vsync", "vfr", "-q:v", "2", outputPattern,
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], { timeout: 30000 });
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for (let i = 1; i <= 4; i++) {
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try {
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const framePath = path.join(tmpDir, `frame-${String(i).padStart(3, "0")}.jpg`);
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const frameBytes = await readFile(framePath);
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const { data: resizedBuffer, mimeType: resizedMime } = await resizeImageForVision(frameBytes, maxDimension);
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const dataUrl = `data:${resizedMime};base64,${resizedBuffer.toString("base64")}`;
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addImageToMap(imageMap, targetId, {
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type: "image_url",
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image_url: { url: dataUrl },
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sourceLabel: `[frame ${i}/4 dari video ${att.filename} (attachment), pesan id=${att.message_id}]`,
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});
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} catch { /* skip */ }
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}
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log.info({ attachmentId: att.id }, "Video frames extracted");
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} catch (ffmpegErr) {
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log.warn({ attachmentId: att.id, error: ffmpegErr instanceof Error ? ffmpegErr.message : String(ffmpegErr) }, "ffmpeg failed");
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} finally {
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try { await unlink(inputPath); } catch { /* ignore */ }
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for (let i = 1; i <= 4; i++) {
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try { await unlink(path.join(tmpDir, `frame-${String(i).padStart(3, "0")}.jpg`)); } catch { /* ignore */ }
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}
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try { await rm(tmpDir, { recursive: true, force: true }); } catch { /* ignore */ }
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}
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}
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async function downloadMediaCandidate(
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candidate: MediaCandidate,
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targetId: string,
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maxDimension: number,
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imageMap: Map<string, MessageImagePart[]>,
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mediaAnalysisMap: Map<string, string[]>,
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): Promise<void> {
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const log = createChildLogger("mediaAnalysis");
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if ((imageMap.get(targetId)?.length ?? 0) >= 8) return;
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if (candidate.customEmojiId || candidate.stickerName) {
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const vck = candidate.customEmojiId
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? makeCustomEmojiCacheKey(candidate.customEmojiId)
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: makeStickerCacheKey(candidate.stickerName!);
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const cached = await getCachedMediaAnalysis(vck);
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if (cached) {
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const existing = mediaAnalysisMap.get(targetId) ?? [];
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existing.push(`[Media analysis for message ${candidate.messageId}] ${candidate.label}: ${cached}`);
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mediaAnalysisMap.set(targetId, existing);
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return;
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}
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}
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if (candidate.stickerName && isStickerCacheReady()) {
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try {
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const cached = await getStickerFromCache(candidate.stickerName);
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if (cached?.imageUrl) {
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addImageToMap(imageMap, targetId, {
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type: "image_url",
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image_url: { url: cached.imageUrl },
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sourceLabel: candidate.label,
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stickerName: candidate.stickerName,
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});
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return;
|
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}
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} catch { /* fall through */ }
|
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}
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const result = await fetchUrlSafely(candidate.url);
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if (result.type !== "image" || !result.data || !result.mimeType) return;
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const { data: resizedBuffer, mimeType: resizedMime } = await resizeImageForVision(result.data, maxDimension);
|
||||
const base64 = resizedBuffer.toString("base64");
|
||||
if (candidate.stickerName) {
|
||||
uploadAndCacheSticker(candidate.stickerName, resizedBuffer, resizedMime).catch(() => {});
|
||||
}
|
||||
addImageToMap(imageMap, targetId, {
|
||||
type: "image_url",
|
||||
image_url: { url: `data:${resizedMime};base64,${base64}` },
|
||||
sourceLabel: candidate.label,
|
||||
stickerName: candidate.stickerName,
|
||||
customEmojiId: candidate.customEmojiId,
|
||||
customEmojiName: candidate.customEmojiName,
|
||||
});
|
||||
}
|
||||
|
||||
async function fetchUrlInline(
|
||||
url: string,
|
||||
targetId: string,
|
||||
maxDimension: number,
|
||||
imageMap: Map<string, MessageImagePart[]>,
|
||||
webTexts: string[],
|
||||
): Promise<void> {
|
||||
const result = await fetchUrlSafely(url);
|
||||
if (result.type === "image" && result.data && result.mimeType) {
|
||||
const { data: resizedBuffer, mimeType: resizedMime } = await resizeImageForVision(result.data, maxDimension);
|
||||
addImageToMap(imageMap, targetId, {
|
||||
type: "image_url",
|
||||
image_url: { url: `data:${resizedMime};base64,${resizedBuffer.toString("base64")}` },
|
||||
sourceLabel: `[gambar dari URL ${url} (inline), pesan id=${targetId}]`,
|
||||
});
|
||||
} else if (result.type === "text" && result.textContent) {
|
||||
webTexts.push(`<web_content url="${escapeXml(url)}">${escapeXml(result.textContent.slice(0, 2000))}</web_content>`);
|
||||
}
|
||||
}
|
||||
|
||||
// ---------------------------------------------------------------------------
|
||||
// Media message preparation
|
||||
// ---------------------------------------------------------------------------
|
||||
|
||||
/**
|
||||
* Download images, run vision analysis, and build the message XML block
|
||||
* for a single media-bearing message. Does NOT make the moderation LLM call.
|
||||
*/
|
||||
export async function prepareMediaMessage(
|
||||
target: MessageRecord,
|
||||
allAttachments: AttachmentRecord[] | undefined,
|
||||
): Promise<PreparedMediaMessage> {
|
||||
const log = createChildLogger("mediaAnalysis");
|
||||
const targetId = target.id;
|
||||
const imageMap = new Map<string, MessageImagePart[]>();
|
||||
const webTextMap = new Map<string, string[]>();
|
||||
const mediaAnalysisMap = new Map<string, string[]>();
|
||||
const maxDimension = config.AI_LLM_IMAGE_MAX_DIMENSION ?? 1024;
|
||||
const content = getAnalysisContent(target);
|
||||
const downloadPromises: Array<Promise<void>> = [];
|
||||
|
||||
// Attachments
|
||||
const msgAttachments = (allAttachments ?? [])
|
||||
.filter((a) => a.message_id === targetId && (a.uploaded_url ?? a.discord_url ?? null) && (a.type.startsWith("image/") || a.type.startsWith("video/")))
|
||||
.slice(0, 8);
|
||||
for (const att of msgAttachments) {
|
||||
downloadPromises.push(downloadSingleAttachment(att, targetId, maxDimension, imageMap));
|
||||
}
|
||||
|
||||
// URLs
|
||||
const urls = extractUrlsFromText(content).slice(0, 3);
|
||||
const urlWebTexts: string[] = [];
|
||||
for (const url of urls) {
|
||||
downloadPromises.push(fetchUrlInline(url, targetId, maxDimension, imageMap, urlWebTexts));
|
||||
}
|
||||
|
||||
// Stickers, embeds, custom emoji
|
||||
const mediaEvidence = extractMessageMediaEvidence(target.metadata);
|
||||
for (const candidate of buildMediaCandidates(targetId, mediaEvidence)) {
|
||||
downloadPromises.push(downloadMediaCandidate(candidate, targetId, maxDimension, imageMap, mediaAnalysisMap));
|
||||
}
|
||||
|
||||
await Promise.all(downloadPromises);
|
||||
if (urlWebTexts.length > 0) webTextMap.set(targetId, urlWebTexts);
|
||||
|
||||
// Vision analysis
|
||||
await Promise.all(
|
||||
Array.from(imageMap.entries()).flatMap(([msgId, images]) =>
|
||||
images.map(async (image) => {
|
||||
const summary = await analyzeSingleMediaImage(msgId, image);
|
||||
const existing = mediaAnalysisMap.get(msgId) ?? [];
|
||||
existing.push(summary);
|
||||
mediaAnalysisMap.set(msgId, existing);
|
||||
}),
|
||||
),
|
||||
);
|
||||
|
||||
// SearXNG
|
||||
let searxngXml = "";
|
||||
const queries = extractSearchQueries(content);
|
||||
if (queries.length > 0) {
|
||||
const results = await Promise.allSettled(queries.map((q) => searchSearxng(q)));
|
||||
const parts: string[] = [];
|
||||
for (let i = 0; i < results.length; i++) {
|
||||
const r = results[i];
|
||||
if (r.status === "fulfilled" && r.value.length > 0) parts.push(formatSearchResults(r.value));
|
||||
}
|
||||
if (parts.length > 0) searxngXml = `\n<web_searches>\n${parts.join("\n")}\n</web_searches>`;
|
||||
}
|
||||
|
||||
// Build XML block
|
||||
const webTexts = webTextMap.get(targetId) ?? [];
|
||||
const mediaAnalyses = mediaAnalysisMap.get(targetId) ?? [];
|
||||
const webContext = webTexts.length > 0 ? `\n${webTexts.join("\n")}` : "";
|
||||
const mediaAnalysisContext = mediaAnalyses.length > 0 ? `\n${mediaAnalyses.join("\n")}` : "";
|
||||
const mediaContext = [
|
||||
mediaEvidence.stickers.length > 0
|
||||
? mediaEvidence.stickers.map((s) => buildStickerTextOnlyWarning(s.name, s.url)).join(" ")
|
||||
: null,
|
||||
mediaEvidence.embeds.length > 0
|
||||
? `[embed evidence: ${mediaEvidence.embeds.map((e) => [e.title, e.description, e.url, e.image, e.thumbnail].filter(Boolean).join(" | ")).join(" || ")}]`
|
||||
: null,
|
||||
].filter(Boolean).join(" ");
|
||||
|
||||
const rep = await initializeUserReputation(target.user_id, target.guild_id);
|
||||
const profile = await getUserProfile(target.user_id);
|
||||
const refXml = await buildReferenceXml(target);
|
||||
|
||||
const messageBlock = `<message id="${escapeXml(target.id)}" user="${escapeXml(target.username)}">\n <user_reputation trust_score="${rep.trust_score}" />${profile ? `\n <user_profile>${sanitizeAiContent(profile.profile_summary)}</user_profile>` : ""}${refXml ? `\n ${refXml}` : ""}\n <content>${escapeXml(content)}</content>${mediaContext ? ` ${escapeXml(mediaContext)}` : ""}${webContext}${mediaAnalysisContext}${searxngXml}\n</message>`;
|
||||
return { targetId, messageBlock };
|
||||
}
|
||||
Reference in New Issue
Block a user