- Add wikipediaClient.ts: native fetch to Wikipedia REST/Action APIs
(search + summary), no extra npm dependency.
- Extract shared Redis cache into cacheStore.ts (decoupled from search).
- Term glossary now uses wikipediaSummary for direct article lookup.
- Remove searxngSearch.ts entirely; drop SEARXNG_BASE_URL config,
add WIKIPEDIA_LANG / WIKIPEDIA_TIMEOUT_MS.
- Rename backend searxngCalls metric to webSearchCalls.
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.
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)
- 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>
- 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
- 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)
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
- 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)
- 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.
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
asepharyana