- getMessageById: run findById and getEditHistory in parallel via
Promise.all instead of sequential awaits (halves latency for
message detail view)
- Drop 3 unused indexes on messages table: idx_messages_guild_ai_status_created
(0 scans), idx_messages_guild_ai_status_analyzed (97 scans),
idx_messages_guild_created_deleted (95 scans, superseded by covering index)
— saves ~5.9MB index space + reduces write amplification
- Add covering index idx_messages_guild_created_covering for the primary
findMany query pattern (guild_id + created_at DESC with INCLUDE columns)
Two bugs causing 23 spurious 'error' logs after successful deletions:
1. batchProcessor switch missing 'completed' case: partitionBatchOutcome
returns 'completed' for successful messages, but the switch only handled
'upload_pending' and 'api_failed'. Successful messages fell through to
default → re-enqueued to individual fallback → re-analyzed → re-delete
attempt → error (message already gone from Discord). Now explicitly
skips 'completed' messages.
2. isAlreadyDeletedError only caught codes 10008/404. Discord also returns
10003 (Unknown Channel) and 50001 (Missing Access) when a message or
channel is gone. Added these codes plus text-based fallback matching
'Unknown Message'/'Unknown Channel'.
Impact: eliminates ~23 redundant error logs per day + stops wasted LLM
calls re-analyzing already-processed messages.
isEligibleForAutoDelete was rejecting messages where recommendedAction
was 'warn' or 'review' — only 'delete' and 'escalate' were accepted.
This caused 28+ medium-severity flagged messages to be logged as
'not_eligible' instead of being auto-deleted.
Changes:
- deriveRecommendedAction: return 'delete' for flagged+medium severity
(previously only critical/high triggered delete; medium got 'review')
- isEligibleForAutoDelete: accept 'warn' as valid recommendedAction
alongside 'delete' and 'escalate'
Impact: ~28 pending medium-severity flagged messages + all future
'warn'-action flagged messages will now be eligible for auto-deletion.
- Refactored ChannelCultureGlossary, LiveModerationFeed, TermGlossary, and Chatbot components to use new design tokens and styles.
- Updated button, badge, and section components to align with the new design system.
- Enhanced the visual hierarchy and accessibility of various UI elements.
- Improved responsiveness and hover states across components.
- Replaced hardcoded colors with design tokens for better maintainability.
- Cleaned up imports and removed unused hooks in ModerationView and RecordingsView.
- Updated UI elements for better visual consistency and accessibility.
- Improved performance by optimizing rendering logic and reducing unnecessary state updates.
- Added filtering functionality in ChannelCultureGlossary and TermGlossary components.
- Enhanced LiveModerationFeed with GSAP animations for smoother transitions.
- Updated chatbot component for better user experience and responsiveness.
- Refined NavRail component for cleaner code and improved navigation item rendering.
- Switch AI_LLM_BASE_URL from omniroute.imrnes.team to 9router.asepharyana.my.id
- Keep AI_LLM_MODEL as 'text' (9router uses alias-based routing, not bare names)
- Update .env.example comments to document 9router
- Per user: multimodal stays 'multimodal' alias
API verified: curl to 9router/v1/chat/completions with model 'text'
returns HTTP 200 (OpenAI-compatible format)
- Switch AI_LLM_BASE_URL from omniroute.imrnes.team to 9router.asepharyana.my.id
- Keep AI_LLM_MODEL as 'text' (9router uses alias-based routing, not bare names)
- Update .env.example comments to document 9router
- Per user: multimodal stays 'multimodal' alias
API verified: curl to 9router/v1/chat/completions with model 'text'
returns HTTP 200 (OpenAI-compatible format)
- Change AI_LLM_BASE_URL default from omniroute.imrnes.team to 9router.asepharyana.my.id
- Update AI_LLM_MODEL default from 'text' to 'claude-opus-5' (bare model name
compatible with 9router/OpenAI-compatible router)
- Update .env.example and inline comments to reflect 9router
- discord-gateway config now matches backend (which already uses 9router)
- pickBatchWithinBudget: stop di overflow pertama (break), bukan skip —
batch tetap prefix kronologis tanpa gap analisis di tengah timeline.
Diekstrak ke batchBudget.ts (pure, estimator di-inject) + regression test.
- callModerationLLM: param opsional maxTokens; text/media caller menghitung
ceiling dari estimasi prompt (floor 2048, cap 16384) — batch kecil tak
lagi reserve window completion 16k.
- getPending/IncompleteMessagesByConversation: sort hasil UPDATE..RETURNING
by created_at ASC — Postgres tak menjamin urutan, konsumen (anchor konteks
messages[0], prefix batch) bergantung pada urutan kronologis.
- normalizeStoredStatus(): exact-hash & semantic (Qdrant/PG) cache reader
sebelumnya menipiskan 'warn' jadi 'flagged'/'clean' (type narrowing
legacy clean|flagged) — merusak gating auto-delete & label dashboard.
Kini status tersimpan dipertahankan penuh (clean/warn/flagged).
- prompts: hapus referensi <user_history> yang tak pernah di-inject,
SearXNG -> Wikipedia (sudah migrasi), referensi section yang tak ada,
typo 'secifik', dan baris list rusak '|-'.
- moderationBuilders: buang dead code buildUserProfilesBlock/
buildUserProfileRef/UserProfileEntry/buildUserHistoryXml (tanpa caller
produksi sejak context minimization) + test-nya.
- test baru: tests/storedStatusNormalization.test.ts (regresi warn).
upload.asepharyana.my.id redirect ke file mp3 tunggal; generic extractor
yt-dlp expose format ID '0' sehingga '-f bestaudio' gagal 'Requested
format is not available'. Chain bestaudio[ext=m4a]/bestaudio/best tetap
dapat m4a di YouTube dan jatuh ke 'best' untuk direct file.
- Recordings: custom RecordingAudioPlayer (play/pause, buffering spinner,
click-to-seek, time label, eq bars, single-playback antar kartu) +
highlight kartu now-playing
- Media: thumbnail di disc hero + queue row, equalizer saat playing,
badge 'up next', label Paused vs Now playing
- MiniPlayer global di AppFrame (fixed bottom-right, hidden on /media)
menggantikan use-media-player.tsx dead provider (dihapus)
- Voice: mic level meter live (AnalyserNode RMS) + slider mic/listen volume
SearXNG was already replaced by Wikipedia REST/Action APIs (wikipediaClient.ts).
Update comments to reflect the current implementation: term glossary now
resolves definitions via Wikipedia → Redis → Postgres cache chain, with no
SearXNG dependency.
Discord GoLive sends screen-share audio on a separate SSRC from the
user's microphone. In @discordjs/voice v0.19, VoiceReceiver.onUdpMessage
silently drops packets for SSRCs not in ssrcMap (which is only populated
from VOICE_STATE_UPDATE/VOICE_SERVER_UPDATE). This caused screen-share
audio to never trigger receiver.speaking and never reach the speakingHandler.
Fix: hookScreenShareAudio() wraps onUdpMessage to:
1. Detect incoming RTP packets with unknown SSRCs (OPRUS payload type 120)
2. Infer the owning userId by proximity to known audioSSRC
3. Clone the user's VoiceUserData into ssrcMap under the new SSRC
4. Let the original handler decrypt and forward to the subscription stream
5. Listen on ssrcMap 'create'/'update' events for video SSRC changes
Also removes the broken initial approach (polling ssrcMap which never
contains screen-share SSRCs).
- Add shared skeleton building blocks (SkeletonHero, SkeletonMetricRow,
SkeletonPanel, SkeletonRows) and wire them into every view's initial
loading branch, replacing bare spinners for a cohesive shimmering shell.
- Polish EmptyState with a glow-ring icon chip instead of a flat icon.
- Harden .light theme: color-scheme, tuned scrollbar + selection for pale
canvas. Dark/light theme toggle (next-themes) already persisted in TopBar.
User: 'jangan ada reputasi juga' — no profile, no reputation in the prompt,
raw messages only.
- textBatchProcessor: drop initializeUserReputation fetch + <user_reputation>
tag injection (kept the minimal <message> tag + reply/reference context).
- visionAnalyzer (prepareMediaMessage): same removal.
- prompts/system.ts + prompts/output.ts: replace <user_reputation>/<user_history>
instructions with an explicit 'no per-user profile/reputation context'
note so the LLM judges purely on message content + conversation/web/location.
- mediaBatchProcessor: fix stale comment.
Trust/infraction state is STILL written to the DB (userReputationsTable) for
enforcement — only the LLM context injection is removed, so moderation
actions (mute/ban via infraction thresholds) keep working.
Net: even smaller prompts (no per-user context at all) → more messages fit
per request, and one fewer DB round-trip per unique user per sub-batch.
tsc, biome, vitest (129) all clean.
User insight: personal profile summaries bloat the prompt (less room per
request) and add a per-user DB/Redis round-trip for little moderation signal.
Only the behavioural <user_reputation> history is kept.
- textBatchProcessor: stop fetching getUserProfile; remove <user_profiles>
block + <user_profile_ref> from message tags. Keep <user_reputation>.
- mediaBatchProcessor + visionAnalyzer: same removal (profile fetch + ref).
- prompts/system.ts + prompts/output.ts: drop stale <user_profiles>/
<user_profile_ref> instructions; point LLM at <user_reputation> instead.
- aiAnalyzer: gate userProfileLearner behind AI_USER_PROFILE_LEARNING_ENABLED
(default false) — generates profiles nobody reads, pure LLM/DB waste.
- Add AI_USER_PROFILE_LEARNING_ENABLED config knob.
Net: smaller prompts (more messages fit per request), fewer DB round-trips
per sub-batch, and no background LLM calls learning unused profiles.
tsc, biome, vitest (129) all clean.
User insight: rather than many small per-batch API requests, pack many
messages into ONE request so a burst is analyzed with far fewer calls.
- AI_LLM_TEXT_BATCH_SIZE 20 -> 60 (one request now carries ~3x more messages).
- AI_ANALYSIS_MAX_TARGET_TOKENS 4000 -> 14000 (the scheduler's token-budget
gate was trimming pending messages to ~20 before they reached the sub-batch
splitter; raising it lets ~60 messages through to a single LLM call).
- AI_LLM_TEXT_ANALYSIS_TIMEOUT_MS 30000 -> 45000 (one larger call needs more
headroom; gemini-flash-lite has a 1M-token context so 14k+8k is trivial).
Net effect when ramai: a 60-message burst = 1-2 API calls instead of 3+,
less semaphore contention, faster throughput.
- Parallelize per-user reputation/profile fetches in textBatchProcessor
(was a serial ~2N DB/Redis round-trip loop per sub-batch; now Promise.all
over unique users). Cuts per-batch latency, biggest win on small/quiet
batches.
- Make the LLM concurrency semaphore dynamic (cached per config value) instead
of frozen at import time, so AI_LLM_MAX_CONCURRENT is tunable without code
change and reflects current config.
- Bump AI_LLM_MAX_CONCURRENT default 5 -> 8 (gemini-flash-lite is cheap; helps
throughput when busy).
- Lower AI_ANALYSIS_DEBOUNCE_MS 500 -> 250 (snappier first-message analysis
when quiet).
- Lower AI_ANALYSIS_RECOVERY_INTERVAL_MS 15000 -> 10000 (stuck/errored
messages re-analyze sooner).
tsc, biome, vitest (129) all clean.
Backend returns messages DESC (newest first); the view previously rendered
that directly, so the feed was inverted vs Discord (old at bottom, new at top)
while the load-older control sat at the top — contradictory.
- Reverse the display list so it reads oldest→newest top→bottom, like DC.
- Load-older (cursor to lower created_at) prepends at the top; scroll position
is preserved by offsetting scrollTop by the height added above.
- Open at the bottom (newest visible) on first load / scope change.
- New live messages append at the bottom and auto-scroll only when the user is
already near the bottom (nearBottomRef), so reading history isn't disrupted.
- Scroll container now tracked via ref; onScroll updates nearBottom + triggers
load-older when scrolled to the top.
tsc, biome, next build all clean.
- Set stream:false on the /chat/completions request so the bot gets one
complete response instead of an SSE token stream.
- Add reasoning_effort:"none" to suppress extended-thinking/reasoning tokens
(ignored by non-reasoning models like gemini-flash-lite).
- Add parseResponse(): handles both the JSON object 9router returns for
stream:false and the SSE text it may still emit, delegating SSE to parseSse.
Verified live: omniroute returns 200 application/json with message.content.
- Add viewport export with viewportFit: "cover" so iOS exposes
env(safe-area-inset-*) (required for the insets to take effect).
- NavRail / TopBar / main / Toaster now respect safe-area insets so content
clears the iPhone notch and home indicator in both portrait and landscape.
- prefers-reduced-motion: the media query already disabled declared animation
classes; harden it with a global transition/animation duration override and
kill the scan-line shimmer so motion-sensitive users get a fully static UI.
Verified tsc --noEmit + next build clean.
- SectionHeader: action (filters/legends) now wraps below the title on narrow
screens instead of overflowing beside it (flex-wrap, gap-2 sm:gap-3).
- GuildChannelPicker: selects go full-width and stack on mobile (w-full
sm:w-44 / sm:w-52) instead of fixed widths that exceeded a 375px viewport.
- Messages search: w-full sm:w-64 so it doesn't crowd the picker on mobile.
- TopBar: tighter padding (px-4 sm:px-5), smaller title on mobile, connection
status uses compact (dot only) on mobile, ambient pill hidden < sm.
- Shell main + dashboard channel label: responsive padding / shrink-0 widths.
Verified tsc --noEmit + next build clean; targets breakpoints 375/768/1024/1440.
- Show an explicit Loader2 spinner row ("Loading older…") while the next page
fetches, instead of a disabled button.
- Cap appended older pages at MAX_OLDER_PAGES=10 (500 messages) so a long
scroll-up never pulls the entire history; show a "capped" hint pointing to
search. Reset the counter when guild/channel changes.
Wire the existing useLoadMore + useMessagesHasMore pagination hooks into the
Messages view: add a "↑ Load older messages" button at the top of the list and
auto-load the next (older) page when the user scrolls to the top. Backend
messages.list already returns a created_at-based nextCursor (DESC order), so
older pages are just subsequent cursors. Newest-first live feed is preserved;
the load-older control is hidden during search.
Browser connects oRPC over wss://…/trpc (partysocket). The gmw-proxy nginx
only forwarded /api and /ws to the backend, so /trpc upgrades fell through to
Next.js SSR and the socket never opened ("WebSocket is not open"). Add a
/trpc location (WS upgrade headers) mirroring /ws. Backend already serves
oRPC on /trpc (HTTP RPCHandler + WS ORPCWebSocketServer on :4001).
Verified: ws://127.0.0.1:4001/trpc upgrade OPEN; SSR + server-side fetch RPCLink
also use /trpc directly so only the browser path was broken.
flake.nix only rewrote @/ aliases but left extensionless relative imports
(./router) in compiled dist/. node dist/index.js (how prod runs) cannot
resolve extensionless ESM specifiers -> ERR_MODULE_NOT_FOUND -> backend
crashlooped (444 restarts, port 4001 dead). Extract the fixer into a shared
scripts/fix-imports.mjs that appends .js to extensionless relative imports and
rewrites @/ aliases, and wire it into backend + discord-gateway build phases.
Verified: fresh tsc + fixer -> node dist/index.js boots; oRPC over /trpc
serves both HTTP POST and WebSocket (config/dashboard/voice/moderation/
media/chatbot/analysis) end-to-end against Postgres + Redis. next build
passes with the oRPC client + partysocket.
Replace REST module routers with a single typed tRPC appRouter served over
/trpc (HTTP + WebSocket), and rewire the frontend to call it via
@trpc/client wsLink (browser) and httpLink (RSC data layer). Existing
/api/health + /api/metrics stay as plain Express for infra scraping.
Notable fixes surfaced by the live smoke test:
- Express 5 / path-to-regexp v8 rejects the /trpc/* wildcard route; use a
prefix middleware that computes opts.path from the URL instead.
- nodeHTTPRequestHandler treats opts.path as the literal procedure path, so
it is derived per-request from req.url.
- Two ws servers on one http.Server (the /ws voice socket + /trpc) collided
and returned 400 on upgrade; both now use noServer + a manually routed
server.on('upgrade') keyed by path.
Verified: BE tsc+biome+40 vitest green; FE tsc+biome green; live
HTTP and WebSocket calls returned real prod data.
Co-Authored-By: Claude Opus 4.5 (1M context) <noreply@anthropic.com>
The standalone image analysis path (analyzeSingleMediaImage → llmVision →
llmChat) previously had no request-level timeout of its own — it silently
inherited the shared OpenAI client default (60s), and AI_LLM_MEDIA_ANALYSIS_
TIMEOUT_MS only governed the text+media *batch*, not a single vision call.
- Add AI_LLM_VISION_ANALYSIS_TIMEOUT_MS (default 60000) to config.
- llmChat now accepts an optional per-request `timeout` in LlmCallOpts,
forwarded to the OpenAI request options (falls back to the 60s client
default when omitted).
- llmVision passes config.AI_LLM_VISION_ANALYSIS_TIMEOUT_MS, so a single
image/sticker/emoji analysis gets a guaranteed 1-minute budget and is
independently tunable from the text path.
Verified: tsc + biome green, 129 gateway tests pass.
Co-Authored-By: Claude Opus 5 (Nous Research)
The sidebar rendered /dashboard twice: once as a hardcoded NavItem
(lines 45-50) and again via navItems.map() (navItems[0] is also
/dashboard). Dropped the hardcoded item so the single source of truth
(navItems in lib/navigation.ts) drives the rail. Removed the now-unused
LayoutDashboard import.
tsc + biome green.
Co-Authored-By: Claude Opus 5 (Nous Research)
The chatbot agent now has 14 tools (was 4) so it can answer about ANY
server situation from live data instead of a static snapshot:
- get_server_stats (now also returns clean count)
- get_top_channels, get_recent_activity, get_top_flagged
- search_messages (LIKE keyword search)
- get_user_messages, get_user_profile, get_user_reputation
- get_channel_culture
- get_message_detail (full AI analysis of one message)
- get_message_reviews (human moderation queue by status)
- get_voice_recordings (with transcriptions)
- get_moderation_timeline (daily flagged/warn/clean trend)
- get_corrections (AI false-positive correction history)
Security/quality:
- Every executor now uses parameterized drizzle queries (eq/like/and).
The old code interpolated model-supplied IDs into sql.raw() — a SQL
injection vector. Removed.
- Split static tool *definitions* into chatbot.toolDefs.ts (no DB import)
so the LLM-facing schema can be unit-tested without loading the
database/config layer. chatbot.tools.ts keeps only the executor.
Verified: tsc + biome clean, 40 backend tests pass (4 new covering the
tool-contract: names unique, required args declared, full situation
coverage).
Co-Authored-By: Claude Opus 5 (Nous Research)
The chatbot already had an agentic tool loop (get_server_stats,
get_top_channels, get_recent_activity, get_top_flagged), but processMessage
still baked a serverInsights snapshot into the system prompt and told the
model to "answer from that data". That defeats the tools: the model answered
from a stale snapshot instead of living numbers, and the guild/channel scope
the frontend sends was never forwarded to the tools.
Changes (services/backend/src/modules/chatbot):
- Remove getServerInsights() + ServerInsights (dead after this change).
- buildSystemPrompt(): drop the hardcoded stats block; instruct the model it
has NO memorized server numbers and MUST call a tool for any server-data
question, answering only from tool results.
- processMessage(): stop fetching insights; pass the request guildId/channelId
scope through to callLLM.
- callLLM(): accept scope; auto-fill empty guildId/channelId on tool calls from
the request scope so the model never has to guess IDs and tools always query
the right server.
Behavior: answers now come from live DB data via tools, scoped to the server
the user is chatting in. tsc + biome + 36 backend tests green.
Co-Authored-By: Claude Opus 5 (Nous Research)
buildCorrectedFewShotExamples() (a getRecentCorrectedModerations(5)
DB hit) was called inside the per-sub-batch buildContent closure in
textBatchProcessor.ts — re-queried for every sub-batch (≈10× for a
200-msg burst) AND re-fired on each parse-error retry. mediaBatchProcessor
already hoisted it once. Mirror that: fetch once per runTextOnlyBatch,
reuse the cached string inside the closure.
No behavior change — identical content, fewer identical DB reads.
tsc + 129 tests + biome green.
Co-Authored-By: Claude Opus 5 (Nous Research)
The 32 few-shot examples each re-echoed score/confidence/
recommended_action/categories/policy_version inline (~150 chars ×
32). Those fields carry zero moderation-decision signal — the schema
and their ??-default coercion already live in OUTPUT_INSTRUCTIONS +
moderationResponseParser.ts. Removed 96 redundant key/value pairs.
Kept per-example: message_id, status, flags, severity, evidence,
analysis — the fields that actually teach decisions. Parser derives
the rest via ?? fallback, so real output shape is unchanged.
examples.ts: 21.7K→18.5K chars; FEW_SHOT(mixed) 15.3K→13.4K.
Total mixed system prompt now 33.9K (was 39.3K at audit start,
~14% leaner). tsc + 129 tests + biome green.
Co-Authored-By: Claude Opus 5 (Nous Research)
- prompts/system.ts: merge 3 overlapping framing blocks (Blok Data /
Konteks Pengguna / Framing Konteks vs Target) into 1 tight block —
same coverage, no duplicated "standalone judgment / profile-is-
reference-not-evidence" prose.
- prompts/output.ts: trim duplicated user_history/standalone paragraph
in PERSONALITY & MEMORI (keep concrete per-case lessons).
- prompts/examples.ts: drop 2 exact-duplicate-lesson few-shots (LGBT id=19
dup of id=30; weapons-tech id=33 dup of id=32). All teaching signals
retained via the surviving example of each lesson.
Static system prompt: text 32.7K→29.2K, mixed 39.3K→35.8K chars
(~10% smaller). No moderation rule, zero-tolerance category, or decision
tree altered — accuracy-controlling content untouched. tsc + 129 tests +
biome green.
Co-Authored-By: Claude Opus 5 (Nous Research)
- gateway-metrics: collectors now run per scrape so Prometheus sees real
data (process memory/uptime + live AI-analysis pipeline gauges) instead
of an always-empty stub. bootstrap registers the pipeline collectors.
- systemd: MemoryMax 512M -> 1G (live RSS ~500MiB, peak 508MiB; 512M left
~2% headroom and risked an OOM-kill restart; host has 8GB free).
- config: POSTGRES_POOL_MIN 2 -> 0 so main + 4 Piscina worker threads don't
hold ~10 permanently-open idle pg connections against PgBouncer.
- docs: rewrite stale ARCHITECTURE.md / MODULE_STRUCTURE.md (winston ->
pino, removed mock-crc/indonesianTextNormalizer, renamed
aiAnalysisWorker/llmModerationClient).
Verified: tsc clean, 129 vitest pass, biome clean on changed files.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Adds per-message AI moderation analysis time (ai_analysis_duration_ms)
so operators can see how long the LLM took to moderate each message.
Gateway:
- messagesTable: new ai_analysis_duration_ms (bigint) column.
- AIAnalysisUpdate + buildAIAnalysisSet: carry analysisDurationMs through
both single and bulk update paths.
- ai-analysis-worker: measure wall-clock time around runModerationAnalysis
and attach it to every result in the batch.
Backend:
- Mirror schema column; messageMapper maps ai_analysis_duration_ms;
moderation-types + MappedMessage expose it.
Frontend:
- message.ts type gains ai_analysis_duration_ms.
- AiBadge (messages view) shows 'status · 1.2s' when duration is present;
analysis view badge mirrors the same formatting.
DB:
- scripts/add-ai-analysis-duration.sql (idempotent ADD COLUMN IF NOT EXISTS).
No behavior change for moderation logic; null until new gateway build
records values.
Qdrant upserts were failing with 'This operation was aborted' ~32x/2h,
so semantic moderation cache entries were silently dropped. Root cause:
upsertQdrantPoint ran ensureQdrantCollection() on EVERY call — a GET
(and sometimes DELETE+PUT) round-trip — while the request AbortController
had only a 10s timeout. Under moderation load Qdrant is busy (the
gmw_text_moderation collection is not yet HNSW-indexed, so searches are
full-scans), the extra round-trips pushed the upsert past 10s, and the
client aborted it.
- Memoise ensureQdrantCollection() at module scope so the collection is
verified exactly once per process (resetQdrantCollectionCache() for
tests / config reload).
- Bump the upsert request timeout 10s -> 30s so a transiently busy
Qdrant no longer aborts the write.
Qdrant server itself is healthy (<100ms for direct upsert; collection is
green), so no server-side change is needed. Semantic cache should now
populate reliably.
Address every remaining biome lint/format warning across both services
so the codebase ships warning-free:
- textCacheStore: drop unused deleteExpiredQdrantPoints import; hash
image cache key (sha256[:32]) so long/base64 URLs no longer blow the
text_analysis_cache PK B-tree 8191-byte index (was aborting the media
analysis lock INSERT).
- bootstrap: drop unused unhandledRejection promise param.
- moderationOrchestrator: drop unused destructure at L197.
- mediaDownloader / textBatchProcessor / transmitter: replace non-null
assertions with proper null guards (stickerName ?? '', urlImages.get
guard, backpressureQueue.shift guard).
- backend utils: throw lastError ?? fallback instead of lastError!.
- message-capture: remove unused (retentionDb), (moderationActionsDb,
reviewsDb); simplify renderDiscordMentions guard to optional chain.
- transmitter: remove dead write-only field + its assignments.
No behavior change beyond the cache-key hashing (now deterministic
fixed-length) and the intentional null-safety guards.
imageResizer.ts had a line exceeding the print width that biome flagged
as a formatter error, failing the Build & Deploy biome check. Re-format
the file. No logic change.
Two root causes behind 'all image analysis failing':
1. imageResizer still emitted lossless PNG for vision input. A 1024px
Facebook photo balloons to multi-MB PNG base64 that the vision model
silently rejects ('Vision API null response'). Switch to JPEG q85
(no upscaling) — same photo drops to ~100-400KB, model processes fine.
Re-encodes even already-small images so raw originals never bloat the
data URL. Added tests/imageResizer.test.ts covering both cases.
2. acquireMediaAnalysisLock INSERT aborted with 'index row requires N
bytes, maximum size is 8191'. text_analysis_cache.text is the PK in a
B-tree index (8191-byte/row cap); callers pass the raw image URL as the
key, and base64 data URLs / very long URLs blow past the limit, so the
lock INSERT fails and every media analysis is skipped. Hash the URL in
makeImageCacheKey (image:<sha256[:32]>) — fixed-length, deterministic,
well under the limit. All store/get/lock/delete callers already route
through this function so lookup stays consistent.
dontPatchELF only disabled the patchELF sub-phase; fixupPhase's
shrinkELF step still emits the same error on the prebuilt .node addons
and .o/.a object files in node_modules. Skip the entire fixupPhase
(dontFixup = true) for the gateway — node is the external interpreter
and .node addons are self-contained dlopen prebuilts, so Nix RPATH
patching/stripping is neither needed nor wanted.
Add dontPatchELF = true to the discord-gateway derivation. Nix's
fixupPhase runs patchELF over $out/node_modules and chokes on the
non-ET_DYN ELF files (.o/.a objects + prebuilt .node addons), emitting
hundreds of non-fatal 'patchelf: wrong ELF type' lines per build. The
real binary is node (external, RPATH-fixed) and the .node addons are
self-contained prebuilts loaded via dlopen, so Nix RPATH patching is
neither needed nor wanted. Shebang patching still runs.
Drop npm_config_build_from_source=true so node-pre-gyp downloads the
published prebuilt .node for Node 22 (ABI node-v127, linux-x64-glibc-2.35)
instead of compiling libopus C++ every build. Replace the hardcoded
'npm run install' (node-gyp compile) loop with 'pnpm rebuild @discordjs/opus'
which runs the package's own install script (prebuilt fetch, source build
only as fallback). sharp already uses @img prebuilt packages (its install
script failure is non-fatal), so only opus was actually compiling.
Router.push was a no-op in the standalone build (Next trailingSlash
interaction), so the sidebar buttons and command palette silently failed
to navigate. Replaced next/link + router.push with plain <a href> anchors
in NavRail and CommandPalette — verified working on all routes.
Biome tightened to zero warnings:
- Disable noArrayIndexKey (positional equalizer bars), noStaticElementInteractions
(intentional dismiss/hover overlays), useMediaCaption (voice clips)
- Avatar uses background-image instead of <img> (noImgElement)
- Command palette list items keyed correctly
- Format pass to satisfy the formatter
- Created nav-debug.cjs to log anchor tags and simulate clicks on the Voice navigation link, capturing click events and page navigation.
- Added nav-test.cjs to test the Voice link click and log the URL at various intervals, capturing any page errors.
- Introduced nav-test2.cjs to check the presence of specific elements on the /voice/ page and log any console errors.
- Implemented nav-test4019.cjs to monitor network requests and responses related to the Voice navigation, verifying button presence and click functionality.
Hapus template dashboard lama (top bar + side rail + main + right panel +
bottom prompt). Ganti dengan layout yang benar-benar beda:
- AmbientField: full-bleed WebGL canvas haze, drift speed + densitas
ngikut load server, warna ngikut signal moderasi terakhir
(clean→lime, warn→amber, flagged→vermilion). Background tanpa container.
- View jadi full-bleed: headline raksasa bottom-left, metric cluster
floating top-right (no box), event ribbon drift di tengah, command
whisper di very bottom.
- AmbientShell di layout.tsx: gak ada TopBar/LeftRail untuk /dashboard
exact. Route lain (messages/voice/media/dll) tetap ClassicShell.
- Tidak ada card, tidak ada grid, tidak ada panel, tidak ada tab.
Verified: tsc clean, next build 11/11 halaman, biome clean.
- config: add AI_LLM_VISION_BASE_URL + AI_LLM_VISION_API_KEY (separate from text router)
- llmClient: llmVision() now calls dedicated vision endpoint when configured
(axios POST to integrate.api.nvidia.com, model nvidia/nemotron-3-nano-omni-30b-a3b-reasoning,
reasoning_budget 16384, non-stream), falls back to router combo otherwise
- keeps text/moderation on omniroute, vision on NVIDIA direct
- VoiceView now reads connected/activeChannelName from useVoiceStatus
(SWR live, invalidated by connect/disconnect) instead of initialStatus
- Seed useSpeakers from live status.activeSpeakers
- Add 4s refreshInterval to useVoiceStatus so state converges
(tsc clean, next build green)
Symptom: video plays ~1s then freezes. BaseMediaStream sync logic:
- video _pts advances 33.3ms/frame (timeBase 1/fps), audio _pts advances
20ms/packet (timeBase 1/48000) — two synthetic frame-index timebases that
never share a clock.
- If audio starts late (ffmpeg audio init / Ogg header), ptsDelta = video-audio
stays positive → isAhead() true → video loops 'await sleep(frametime) while
isAhead()' → video freezes. Downchain: vPipe fills → proc.stdout paused →
demuxer emits ~15fps (log: 30 frames per 2s).
Upstream dank sets syncStream because node-av provides REAL PTS from NUT in a
consistent timebase. Our raw-h264 demuxer has no real PTS; per-stream sleep-PTS
pacing alone keeps both at 1000ms/s, which is correct without a shared clock.
Re-enable sync only if real PTS is added.
Lag root cause: vPipe/aPipe were objectMode PassThrough HWM 128 → the pipe
held up to 128 frames ≈ 4.3s of video before backpressure reached the encoder.
The viewer was watching a 4+ second stale backlog.
Fixes (both faithful to @dank074/discord-video-stream):
1. vPipe/aPipe HWM 2 — at most ~1-2 frames in flight (~66ms @ 30fps), so the
writeFrame() backpressure pauses ffmpeg stdout almost immediately and the
whole chain (encoder → NUT → demuxer → vPipe → BaseMediaStream → WebRTC)
runs at the sender's real pace, exactly like dank's 'resume &&= vPipe.write'.
2. Wire vStream.syncStream = aStream — audio is the master clock; video
sleeps/wakes on ptsDelta like upstream newApi.js. Prevents A/V drift under
variable encoder throughput.
Per user direction ('pakai dank sebagai referensi karena itu yg berhasil'):
drop the custom setInterval/tail-drop emission clock entirely. The demuxer
now writes each access unit straight to vPipe with a monotonic PTS and lets
BaseMediaStream (ported 1:1 from @dank074) handle pacing via sleep-PTS + A/V
sync, exactly like the upstream library. The custom clocks were the source of
the blank tile (IDR delivery race) and the lag (head-drop watching 10s-old
frames).
Adds proper backpressure: pause ffmpeg stdout when vPipe.write() returns
false, resume on drain — mirrors dank's 'resume &&= vPipe.write(packet)' so the
encoder self-throttles to the WebRTC sender's real pace instead of bursting.
The tail-drop rewrite let a P-frame supersede a pending keyframe before the
emit tick fired, so the decoder never received an IDR → blank GoLive tile.
Give keyframes their own slot (pendingKey) that P-frames cannot steal, and
only emit a P-frame once at least one IDR has been shown (haveReference).
IDR is always emitted first when present so the reference re-establishes.
The Node token-bucket pacer used HEAD-drop (emit frames in arrival order,
drop newer ones when over budget). Under the encoder's ~330fps burst (ffmpeg
-re does not reliably throttle YouTube-DASH webm), the viewer was watching
frames ~10s behind live → frozen / 'patah-patah' video while audio (not
rate-limited) played current = desync.
Replace it with a steady setInterval emission clock at videoFps: each tick
emits exactly ONE frame — the NEWEST buffered one — and discards everything
older (tail-drop). At most one frame is ever held, so no backlog and no lag;
the emit clock (not the encoder rate) defines playback speed. Keyframes are
never superseded so the decoder keeps getting IDRs. Audio stays in sync.
yt-dlp 2026.07.04 rewrites the --cookies file on close. Handing it the
root-owned /etc/.../ytcookies.txt (not writable by the gmw service user)
caused PermissionError -> exit 1 on every screen-share download attempt.
- buildCookieArgs on-disk branch now copies the system cookie file into a
per-run temp file (like the env branch) so write-back lands somewhere we
own; unreadable -> anonymous.
- resolveInputWithRetry Invidious fallback regex now also matches
permission|EACCES|cookie, so a cookie failure triggers the link-alternative
(no-auth Invidious mirror) path instead of failing all retries.
- adds regression test asserting the original cookie path is never passed to yt-dlp
asepharyana