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perf(ai-moderation): drop personal user-profile descriptions from context

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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.
This commit is contained in:
asepharyana
2026-08-16 19:56:27 +07:00
parent 4cf5b87f2b
commit aa280c48b7
7 changed files with 39 additions and 81 deletions
Download Patch File Download Diff File Expand all files Collapse all files
services/discord-gateway/src/modules/ai-moderation/visionAnalyzer.ts
+2 -11
View File
@@ -63,7 +63,6 @@ import {
} from "./mediaDownloader.js";
import {
buildReferenceXml,
buildUserProfileRef,
escapeXml,
formatReputationAttrs,
getAnalysisContent,
@@ -85,7 +84,6 @@ import {
} from "./searxngSearch.js";
import { buildTermGlossaryBlock } from "./termGlossary.js";
import { extractUrlsFromText } from "./urlFetcher.js";
import { getUserProfile } from "./userProfileStore.js";
import { initializeUserReputation } from "./userReputationStore.js";
// ---------------------------------------------------------------------------
@@ -401,21 +399,14 @@ export async function prepareMediaMessage(
.join(" ");
const rep = await initializeUserReputation(target.user_id, target.guild_id);
const profile = await getUserProfile(target.user_id);
const refXml = await buildReferenceXml(target);
// Profile is emitted ONCE per batch in a <user_profiles> map (see
// mediaBatchProcessor); here we only reference it to avoid repeating the
// full summary on every message of the same user.
const profileRef = profile?.profile_summary?.trim()
? buildUserProfileRef(target.user_id)
: "";
// Rich reputation — attrs only, no user history injection (per channel context preference)
// Only the behavioural <user_reputation> history is injected; personal profile descriptions are omitted (see textBatchProcessor).
const repAttrs = formatReputationAttrs(rep);
const repXml = `<user_reputation ${repAttrs}/>`;
const isBot = resolveIsBot(target);
const isEdited = resolveIsEdited(target);
const messageBlock = `<message id="${escapeXml(target.id)}" user="${escapeXml(resolveDisplayName(target))}" time="${new Date(target.created_at).toISOString()}"${isBot ? ` bot="true"` : ""}${isEdited ? ` edited="true"` : ""}>\n ${repXml}${profileRef ? `\n ${profileRef}` : ""}${refXml ? `\n ${refXml}` : ""}\n <content>${escapeXml(truncateForAi(content))}</content>${mediaContext ? ` ${escapeXml(mediaContext)}` : ""}${webContext}${mediaAnalysisContext}${searxngXml}${glossaryCtx}\n</message>`;
const messageBlock = `<message id="${escapeXml(target.id)}" user="${escapeXml(resolveDisplayName(target))}" time="${new Date(target.created_at).toISOString()}"${isBot ? ` bot="true"` : ""}${isEdited ? ` edited="true"` : ""}>\n ${repXml}${refXml ? `\n ${refXml}` : ""}\n <content>${escapeXml(truncateForAi(content))}</content>${mediaContext ? ` ${escapeXml(mediaContext)}` : ""}${webContext}${mediaAnalysisContext}${searxngXml}${glossaryCtx}\n</message>`;
return { targetId, messageBlock };
}