Root cause: makeImageCacheKey() only hashed the first 128 chars of the
data URL. Since all resized images use the same MIME prefix
('data:image/png;base64,') + identical base64 header bytes, nearly every
image got the same 16-char hash → 'image:<same-hash>' → all images reused
the first cached vision analysis (often a gambling-detection verdict).
Fix: hash the entire data URL instead of just the prefix. Verified
114 stale 'image:' entries + 745 stale 'phash:' entries purged from prod
DB. tsc --noEmit clean, 133 tests pass.
- Add term_glossary_cache table + migration 0014: resolved definitions are
stored permanently (definitions rarely change); misses stay ephemeral in
Redis/LRU with 1h TTL so transient failures get retried
- Lookup flow: LRU -> Redis -> Postgres (permanent) -> live SearXNG; DB hits
re-warm the fast caches; stale Redis miss sentinels no longer shadow DB
- Rate-limit-aware live lookups: concurrency 2 + stagger, retry once on empty
results, strict definition filter (Wikipedia preferred, rejects
disambiguation/ads/translate-homepages)
- Make SEARXNG_BASE_URL configurable via env (default unchanged)
Root cause (3rd layer after 50371bd + 4f4c435): a vision model run
(2026-08-10) returned 'Maaf, saya tidak melihat gambar apapun yang terlampir...'
and that text was cached as a VALID vision_llm result (image + phash keys,
24h/7d TTL). Every subsequent analysis of the same image (same hash/phash)
hit the poisoned cache, so image analysis looked broken forever even though
9router responded fine — the moderation LLM wrote 'lampiran yang gagal
terbaca' from a cache hit.
Also: mimo via 9router streams reasoning in delta.reasoning +
delta.reasoning_details[].text (content:"") — extractChunkText only read
delta.reasoning_content, so those runs aggregated empty → 'Vision API null
response' (observed 08:54/09:07/09:38).
Fixes:
- llmClient.extractChunkText: fall back to delta.reasoning and
reasoning_details[].text (mimo), on top of reasoning_content (gemma).
- visionAnalyzer: isNoImageSeenText() detects 'no image' style outputs;
such results are NEVER cached, and poisoned entries are purged when hit
(LRU/DB/phash) so re-analysis actually re-runs vision.
- Tests: reasoning/reasoning_details extraction + isNoImageSeenText
(Indonesian + English, no false positives on real descriptions).
Root cause (2nd layer after 50371bd): the analysis worker could pick up an
image message while its attachment upload was still in flight
(upload_status='pending'). downloadAndExtractFrame then fell back to the
Discord CDN URL (cdn.discordapp.com), which often 404s for old/purged links,
and 'if (!res.ok) return' silently dropped the image — no log, no vision
call, empty image map, and the LLM produced a text-only verdict like
'lampiran yang gagal terbaca oleh sistem'.
Fixes:
- ai-analysis-worker: skip targets whose attachment upload is still pending
(both batch + individual paths) — they stay ai_status='pending' and the
next 15s cycle analyzes them after the upload lands.
- mediaDownloader.downloadAndExtractFrame: try uploaded_url first, then
discord_url as fallback; log non-OK responses (status + host) instead of
silently returning; log when all candidate URLs fail.
Root cause: 9router combo 'multimodal' routes to cloudflare-ai/@cf/google/
gemma-4-26b-a4b-it which streams ALL output in delta.reasoning_content
(content:"") and finishes with 'length' at max_tokens. llmClient only read
delta.content, so llmVision returned empty → every image moderation fell back
to text-only analysis ('Meskipun analisis gambar gagal' in every ai_analysis).
Fix: extractChunkText() prefers delta.content then falls back to
delta.reasoning_content (also handles message/text/response fields), with
unit tests for the exact 9router chunk shape. Verified live against a real
DB image: oc/mimo-v2.5-free (new first model in the multimodal combo) returns
a proper description in delta.content.
- <message> targets now carry time (ISO), repetitions (N identical short texts = spam signal), bot and edited flags; escape id/user XML
- rich <user_reputation>: total_infractions, clean_streak, last_offense_days_ago, repeat_offender (7-day window)
- <user_history> with last flagged messages for repeat offenders (wires dead getUserRecentInfractions)
- <user_profile as_of> staleness signal; <location_context topic> from captured channel topic
- prompt framing + output instructions teach the LLM to use the new signals without treating history as proof
- tests: contextEnrichment.test.ts (13) + topic cases in conversationContext.test.ts
When the ONLY violation is offensive_username (message content clean):
- Message is NOT deleted (nickname-only violation bypasses auto-delete)
- Member's server nickname is reset to default username via
setNickname(null) (Discord shows the global username again)
- Action 'reset_nickname' logged to moderation_actions; cooldown
10min per guild:user (LRU) so repeated messages by same member
don't hammer the Discord PATCH
- Config: AUTO_NICKNAME_RESET_ENABLED / AUTO_NICKNAME_RESET_COOLDOWN_MS
- resolveDisplayName(): member.displayName from captured metadata,
falls back to global username
- Applied to context lines, target message blocks, and media message
blocks — LLM sees the name the channel actually sees (nickname can
carry moderation signal itself)
- Conversation context recency gates (GAP_MS/MAX_AGE_MS): drop stale
messages before silence gaps; cold_start anchor + flow descriptor
tells LLM whether conversation is ongoing or restarted
- [location] block: channel name, thread name, nsfw/age flags from
captured metadata (thread names instead of bare IDs)
- Link media -> multimodal: text-batch URL fetches that resolve to
images now run vision analysis (bounded 15s) and switch prompt to
mixed mode; <web_content> gains og:title for page context
- pnpm-workspace.yaml: approve sharp build script (unblocks install)
Audit lanjutan: 6x 'LLM API request failed: Request was aborted' per jam.
Root cause: 9router/omniroute SELALU balas SSE (data: chunks) walau request
tanpa stream:true — SDK OpenAI non-stream menunggu FULL body sebelum parse,
jadi batch moderasi besar yang upstream-nya lambat kena timeout 30-60s dan
di-abort. llmClient sudah punya agregasi streaming (chunks → ChatCompletion).
Fix: stream:true di llmCaller (moderasi batch/individual), llmVision,
cultureLearner, userProfileLearner. Verified: SDK stream test 806ms vs
sebelumnya abort. Caller lain (recovery worker dll) lewat llmCaller sama.
Audit log produksi (sejak deploy13:38) menemukan 3 isu:
1. mediaDownloader.ts spawn /usr/bin/ffprobe + /usr/bin/ffmpeg (path keras) —
ENOENT di Nix karena binary cuma di ffmpeg-headless closure. Pakai
PATH-resolved ('ffprobe'/'ffmpeg') seperti voice-recording module
(ffmpegProcess.ts/transmitter.ts) — 5 media warning hilang.
2. individualFallbackProcessor log error 'Success' di level50 tiap fallback
BERHASIL (logModerationError dengan new Error('Success')) — ganti
logger.info dengan verdict yang sama; error log cuma untuk error asli.
3. moderationResponseParser: strip frasa penutup generik ('Tidak ada
indikasi pelanggaran.') yang masih sering dikeluarkan LLM walau prompt
melarang (277/1486 analisis mengandung frasa, termasuk hari ini).
sanitizeGenericCleanCloser hanya mencocok frasa di AKHIR, teks substantif
tetap utuh. Unit test: 6/6 pass.
QoL lanjutan dari fix60084b3: content pesan mentah masih nampilin
snowflake (<@&roleid>, <@userid>, <:emoji:id>) di log moderasi dan
prompt LLM. Sekarang dirender ke nama yang bisa dibaca:
- Gateway capture: metadata menyimpan mentionedRoles + mentionedUsers
(id+name) dari message.mentions, disimpan ke metadata JSON
- renderDiscordMentions(): <@&id> -> @RoleName, <@id> -> @Username,
<:name:id> -> :name:, fallback @role/@user — dipakai di
conversationContext (konteks LLM) dan moderationBuilders
(getAnalysisContent) sehingga LLM lihat nama role/user beneran,
bukan placeholder generik
- Frontend renderMessageContent() (mirror gateway) dipasang di semua
tempat nampilin content: message-card, message-detail(-view),
search-overlay, search-panel, users/channels section, live-stream,
mod-queue, review list; sticker-only message tetap [Sticker: name],
pesan teks+sticker kini ikut nampilin nama sticker
- tsc --noEmit PASS di gateway & frontend; renderDiscordMentions
diverifikasi manual (6 kasus: role/user/emoji/unknown/plain)
- Deleted the text analysis prompt constants and helpers as they are no longer needed.
- Added batch search functionality for Qdrant to optimize vector searches.
- Implemented methods for deleting expired Qdrant points and invalidating cache based on content hash.
- Updated text batch processor to use new timeout configurations and modified content building for moderation prompts.
- Enhanced text cache store to support new Qdrant integration and improved cache invalidation logic.
- Introduced a new user reputation model with a more nuanced trust scoring system, including penalties and rewards for user behavior.
- Added unit tests for the new trust model to ensure correctness of penalty and trust gain calculations.
- Updated configuration schema to reflect new timeout settings and removed deprecated OpenAI moderation keys.
New qdrantClient.ts (zero-dep fetch REST): ensure collection with cosine
distance (auto-recreate on vector-size change), upsert point w/ verdict
payload, search w/ expires_at filter + score threshold.
textCacheStore: when QDRANT_URL set, embeddings are upserted to Qdrant
(primary) and searched there first; Postgres embedding column remains as
legacy fallback for pre-Qdrant rows. Config: QDRANT_URL/COLLECTION/API_KEY.
QDRANT_URL already in repo .env; added to VPS env + GATEWAY_ENV secret.
OpenAI SDK v6 defaults to encoding_format=base64; llama-nemotron-embed
(Nvidia-backed) returns 400 'do not support base64'. Semantic cache was
silently disabled in prod. encoding_format: 'float' fixes it.
TS compiled this fine, but the JS spec forbids mixing || and ??
without explicit parens; Node threw 'Unexpected token ??' at startup,
crash-looping gmw-discord-gateway (restart counter 250). Wrap the
fallback chain in parens so the expression is valid.
Root cause: ai-analysis-worker read llmResult.explanation and
llmResult.toxicityScore — fields the LLM pipeline never produces
(canonical AnalysisResult uses analysis/score). Every message fell back
to the bare template "Tidak ada indikasi pelanggaran." and the stored
score was always 0.
- Map analysis/score correctly; fallback now quotes the message content
- Prompt: ban generic analysis phrasing, require reply context
- LLM context: include replied-to message content (metadata.reference)
so the model can explain what the user is replying to
- Frontend: show thread/channel names from metadata instead of raw IDs
(message card, detail views, search overlay); detail panel now
displays the ai_analysis text
- Auto-delete log/DM include the descriptive analysis as the reason
Delete fastClassifier.ts (manual regex patterns for phone/email/IP/crypto/
spam/toxicity) and simpleFallback.ts. These hardcoded patterns were the
source of false positives (Discord emoji snowflakes matched phone_number,
URL digits matched phone, etc.) and produced heuristic verdicts whenever
the LLM failed.
New flow: Message → LLM (with conversation context, media evidence, user
reputation) → verdict. On LLM failure the message is marked 'error' and
retried by the recovery worker — no heuristic verdicts, ever.
Discord markdown tokens (custom emoji/mentions/timestamps) are normalized
to readable placeholders ([emoji:name], @user, @role, #channel, [time])
before reaching the LLM via discordTokens.ts.
Custom emoji (<:name:id>), user/role/channel mentions and timestamps embed
long numeric snowflakes that tripped the phone_number / personal_info /
ip_address_sharing patterns — e.g. <:mambotongue:1463255254220148939> was
flagged as phone_number. Strip Discord markdown tokens before pattern
matching and require phone matches to not sit inside a longer digit run.
Build & Deploy / build-and-push (backend) (push) Failing after 35s
Build & Deploy / build-and-push (discord-gateway) (push) Failing after 25s
Build & Deploy / build-and-push (proxy) (push) Failing after 25s
- Remove pnpm workspace, moon repo, and all monorepo tooling
- Delete packages/shared/, embed shared code directly into each service
- Copy packages/shared/src/* -> services/backend/src/shared/ and services/discord-gateway/src/shared/
- Replace all @bete/shared imports with @/shared/ path alias
- Remove @bete/shared workspace dependency from both services
- Update root package.json scripts from --filter to --prefix
- Rewrite Dockerfiles to build each service standalone
- Clean up biome.json, .gitignore, remove root drizzle.config.ts
Build & Deploy / build-and-push (backend) (push) Successful in 25s
Build & Deploy / build-and-push (proxy) (push) Successful in 3m46s
Build & Deploy / build-and-push (discord-gateway) (push) Failing after 4m42s
- Cast llmResult through unknown to handle type mismatch between
shared AnalysisResult and layer-specific local type
- Exclude src/**/archive/** from tsconfig to prevent dead code errors
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Build & Deploy / build-and-push (discord-gateway) (push) Failing after 28s
Build & Deploy / build-and-push (backend) (push) Successful in 1m46s
Build & Deploy / build-and-push (proxy) (push) Successful in 1m37s
\U escapes are not valid in JavaScript/TypeScript regex literals.
Use new RegExp() constructor to avoid TS parser issues.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-07-28 15:10:47 +07:00
DeveloperandClaude Opus 4.8 (1M context) <noreply@anthropic.com
Full frontend redesign with glassmorphic dark theme, floating top nav,
Live2D mascot, split-pane messages, and Ops Center dashboard.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com
Build & Deploy / build-and-push (discord-gateway) (push) Failing after 2m22s
Build & Deploy / build-and-push (backend) (push) Failing after 3m22s
Build & Deploy / build-and-push (proxy) (push) Successful in 1m36s
Build & Deploy / deploy (push) Skipped
- Consolidate all DB schema definitions into packages/shared as single source of truth
- Migrate backend from raw SQL to Drizzle ORM across all modules
- Extract frontend inline UI into separate component files
- Refactor discord-gateway circuitBreaker into conversationState + moderationState
- Convert messageStore to Proxy singleton pattern
- Add validateBody/validateQuery middleware + Zod schemas for API endpoints
- Modernize Docker builds with multi-stage + pnpm deploy
- Migrate CI/CD from deployment to image-based pipeline
- Remove 60+ unused/dead files (~15K lines)
- Update color scheme from sky-blue to teal-cyan
- Move DB connection management to @bete/shared/database
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- Added new dependencies for Next.js and lucide-react in pnpm-workspace.yaml.
- Refactored DashboardPage component to improve readability and error handling.
- Enhanced Header component to display error status with an alert icon.
- Updated MobileTabBar and Sidebar components to use a centralized tabs definition.
- Improved ChannelsView in dashboard-panel to handle channel fetching more cleanly.
- Fixed ActiveSpeaker type to use camelCase for userId.
- Updated MessagesPanel to handle guildId checks more gracefully.
- Adjusted API calls in dashboard and messages to align with backend expectations.
- Refined type definitions across various interfaces for consistency and clarity.
- Fix noImplicitAnyLet: add type to let match variable
- Fix noAssignInExpressions: use matchAll() + for-of instead of while
- Suppress useExhaustiveDependencies in mascot scroll effect
- Suppress useSemanticElements for message card click handler
Two-layer fix for forwarded messages showing as empty/clean:
Layer 1 (messageMetadata.ts): getReferencedMessageContent() now falls
back to message.messageSnapshots Collection when channel.messages.cache
lookup fails. Discord stores forward content in message_snapshots API
field, not in message.content.
Layer 2 (moderationBuilders.ts): buildReferenceXml() now parses msg.
metadata JSON to extract reference.content when DB getMessageById()
fails (cross-server forwards not in local DB).
Previously: forward messages captured with empty parentContent →
LLM saw no reference text → '99% confidence, pesan kosong'.
Now: forward content flows through capture → metadata → analysis.
- Previously: text+media message went ONLY to media array → text waited for vision
- Now: text part goes to text batch (immediate LLM analysis), media parallel
- DB update is idempotent — second write to same message_id overwrites
- User sees text moderation results instantly, media follows when ready
- text-only and media analysis now run concurrently via Promise.all
- text no longer blocks on media download + vision analysis
- each path independently saves to DB when its own results are ready
- same batch still uses single context fetch + attachment lookup
- Remove shouldSearchContent() trigger gate — search runs on all messages
- extractSearchQueries() now extracts from ANY message, not just trigger-matched
- Redis cache (24h TTL) prevents redundant searches for same query
- initSearxngCache() lazy-connects via config.REDIS_URL
- Cache miss→API, hit→skip — fire-and-forget writes
- Both text batch + media path simplified
- Remove hardcoded hentai title lists (Boku no Pico, Euphoria, etc.) from prompt
- Remove hardcoded SARA examples from prompt (Kitabonia, etc.)
- Prompt now tells LLM to use <web_searches> as evidence instead of hardcoded knowledge
- Evidence priority: searxng > web_content > media_analysis > internal model
- Code-side triggers in searxngSearch.ts still filter which messages to search
- LLM makes final decision based on search results, not static lists
- Video frame extraction via ffmpeg (4 key frames per video → vision LLM)
- Video display in FE MessageCard with HTML5 <video> player
- Reply/forward/crosspost indicator in FE + pipeline in DG/BE
- Fix: missing sanitizeAiContent + escapeXml in media path (prompt injection)
- Optimize: text-only batch results saved to DB immediately, no longer wait for media analysis
- BE mapper/schema/repo: add reference fields (is_reply, is_forward, etc.)
- userProfileLearner.ts: filter query to only clean messages (eq ai_status='clean')
to prevent profile contamination from flagged content. Also select channel_id
to group messages by channel in prompt, enabling channel-aware personality
summarization (user may behave differently across channels).
- llmModerationClient.ts (runSimpleTextFallback): inject user profile into
both the classify prompt and the reason prompt, so even the last-resort
fallback path has personality/memory context instead of being blind.
asepharyana