feat(ai-moderation): add user profile self-learning system

Add user_profiles table, store, and background learner worker that summarizes user communication style, topics, and personality. - New user_profiles table (user_id PK, guild_id, profile_summary, last_analyzed_at) - userProfileStore.ts — CRUD (get/update) following channelCultureStore pattern - userProfileLearner.ts — background worker: queries 100 recent msgs per user, calls LLM for personality summary, updates every 12h - Inject <user_profile> XML tag per-message in moderation prompt - Start worker alongside cultureLearner in aiAnalyzer.ts - Migration 0008 for user_profiles table Co-Authored-By: Claude <noreply@anthropic.com>
2026-06-12 20:11:34 +07:00
parent 6effb51b5d
commit fbc2184c6e
8 changed files with 270 additions and 2 deletions
@@ -0,0 +1,138 @@
+import { createChildLogger } from "@bete/shared/logger";
+import { and, desc, eq, sql } from "drizzle-orm";
+import { config } from "../../shared/config/config.js";
+import { getDatabase } from "../../shared/database/drizzle.js";
+import {
+  messagesTable,
+  userProfilesTable,
+} from "../../shared/database/schema.js";
+import { updateUserProfile } from "./userProfileStore.js";
+import { llmChat } from "./llmClient.js";
+
+const PROFILE_LEARNING_INTERVAL = 1000 * 60 * 60 * 12; // 12 hours
+const log = createChildLogger("userProfileLearner");
+
+async function learnUserProfile(
+  userId: string,
+  guildId: string,
+): Promise<void> {
+  const db = getDatabase();
+
+  // Get recent messages for this user
+  const recentMessages = await db
+    .select({
+      content: messagesTable.content,
+    })
+    .from(messagesTable)
+    .where(
+      and(
+        eq(messagesTable.user_id, userId),
+        eq(messagesTable.guild_id, guildId),
+      ),
+    )
+    .orderBy(desc(messagesTable.created_at))
+    .limit(100);
+
+  if (recentMessages.length < 10) {
+    log.debug({ userId }, "Not enough messages to learn user profile");
+    return;
+  }
+
+  const messagesText = recentMessages
+    .reverse()
+    .map((m) => m.content)
+    .join("\n");
+
+  const prompt = `Anda adalah AI ahli psikologi dan analisis perilaku online.
+Tugas Anda adalah merangkum profil kepribadian seorang pengguna berdasarkan
+riwayat pesan-pesan mereka di server Discord.
+
+Pesan-pesan terakhir dari user "${userId}":
+<messages>
+${messagesText}
+</messages>
+
+Berdasarkan pesan-pesan di atas, buatlah ringkasan singkat (maksimal 3 paragraf)
+mengenai:
+1. Gaya komunikasi (formal/casual/teknis/bercanda/serius)
+2. Topik-topik yang sering dibahas
+3. Kepribadian dan karakter yang terpancar
+4. Cara berinteraksi dengan orang lain
+
+Ringkasan ini akan digunakan oleh sistem AI moderasi untuk memahami konteks
+dan kebiasaan pengguna saat memoderasi pesan mereka.
+Jangan menambahkan teks basa-basi, langsung berikan ringkasannya.`;
+
+  try {
+    const completion = await llmChat({
+      messages: [{ role: "user", content: prompt }],
+      max_tokens: 500,
+      temperature: 0.7, // Higher temp for summarization
+      retries: 2,
+    });
+
+    if (!completion) throw new Error("Empty response from LLM");
+    const text = completion.choices[0]?.message?.content?.trim();
+    if (!text) throw new Error("Empty response from LLM");
+
+    await updateUserProfile(userId, guildId, text);
+    log.info(
+      { userId, guildId },
+      "Successfully learned and updated user profile",
+    );
+  } catch (error) {
+    log.error({ userId, error }, "Failed to learn user profile");
+  }
+}
+
+export async function runUserProfileLearningCycle(): Promise<void> {
+  const db = getDatabase();
+  log.info("Starting user profile learning cycle");
+
+  try {
+    // Find users that haven't been profiled recently
+    // We query distinct user_id with enough messages and stale/no profile
+    const staleUsers = await db.execute(sql`
+      SELECT m.user_id, m.guild_id
+      FROM (
+        SELECT user_id, guild_id, COUNT(*) as msg_count
+        FROM messages
+        GROUP BY user_id, guild_id
+        HAVING COUNT(*) >= 10
+      ) m
+      LEFT JOIN user_profiles p ON m.user_id = p.user_id
+      WHERE p.last_analyzed_at IS NULL
+         OR p.last_analyzed_at < ${Date.now() - PROFILE_LEARNING_INTERVAL}
+      LIMIT 50
+    `);
+
+    for (const row of staleUsers.rows || staleUsers) {
+      const userId = String(row.user_id);
+      const guildId = String(row.guild_id);
+      await learnUserProfile(userId, guildId);
+    }
+  } catch (error) {
+    log.error({ error }, "Error in user profile learning cycle");
+  }
+}
+
+let profileInterval: NodeJS.Timeout | null = null;
+
+export function startUserProfileLearnerWorker(): void {
+  if (!config.AI_ANALYSIS_ENABLED) return;
+  if (profileInterval) return;
+
+  // Run once on startup after 1 minute, then every 1 hour
+  setTimeout(() => {
+    runUserProfileLearningCycle().catch((e) => log.error(e));
+  }, 60000);
+
+  profileInterval = setInterval(
+    () => {
+      runUserProfileLearningCycle().catch((e) => log.error(e));
+    },
+    1000 * 60 * 60,
+  ); // Check every hour for users that reached 12h expiry
+
+  log.info("Started user profile learner worker");
+}