feat(gmw): moderation explainability + semantic message search

- Persist structured verdict (flags/severity/confidence/evidence) on moderation_actions so the public web can show WHY a message was moderated. - Add a persistent Qdrant archive collection (gmw_message_archive); embed every captured message at capture time (fire-and-forget, best-effort). - Public semantic search over the archive (backend oRPC + FE toggle on the messages view). Both features are read-only/public and fully automatic. Migration: 0015_add_moderation_explainability.sql
2026-08-18 15:11:01 +07:00
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+# GMW — Moderation Explainability (#1) + Semantic Search (#3) Implementation Plan
+
+> **For Hermes:** Use subagent-driven-development to implement task-by-task.
+> Hard constraint from user (2026-08-18): web is PUBLIC, read-only, for USERS not admins. Moderation MUST stay FULLY AUTOMATIC. Rules stay in CODE (no per-channel config UI).
+
+**Goal:** Make GMW transparent (users see why a message was moderated) and searchable (users can semantic-search the message corpus), via two fully-automatic, code-driven, read-only-public features.
+
+**Architecture:**
+- **#1 Explainability:** Persist the structured moderation verdict that already exists in `AnalysisResult` (`flags[]`, `categories[]`, `severity`, `confidence`, `evidence[]`) into new columns on `moderation_actions`, surface them through the existing public moderation oRPC + the existing public `moderation` dashboard view. No new behavior — only new *data* + new *read* paths.
+- **#3 Semantic Search:** Add a SECOND persistent Qdrant collection (`gmw_message_archive`) keyed by message id (NOT the TTL cache). Embed each captured text message at capture time (reuse `embedText`) and upsert. Add a public `messages.semanticSearch` oRPC + a read-only search UI on the public `messages` view. Best-effort / non-blocking — embed failures never affect moderation or capture.
+
+**Tech Stack:** TypeScript (discord-gateway + backend + frontend monorepo), Drizzle ORM + Postgres (PgBouncer on imrnes), Qdrant (100.121.180.82:6333), Next.js 16 App Router + shadcn/ui, oRPC over `/trpc`. pnpm. Deploy via GitHub Actions Nix build + `systemctl restart`.
+
+**Critical existing facts (verified in repo):**
+- `AnalysisResult` shape (`src/modules/ai-moderation/ai-analysis-worker.ts:55`): `messageId, status, flags[], categories[], severity, confidence, recommendedAction, score, analysis, correctedFlags?`. The shared `AnalysisResult` (`src/shared/moderation-types.ts:142`) ALSO has `evidence?: string[]` and `policyVersion?: string`. **THESE ARE ALREADY COMPUTED but only logged, never persisted to `moderation_actions`.**
+- `moderation_actions` schema is DEFINED TWICE with a divergence:
+  - `src/shared/database/schema.ts:638` → `pgModerationActionsTable` (authoritative, has `reset_nickname` in `action_type` enum).
+  - `src/shared/database/schema/messages.ts:25` → another `pgModerationActionsTable` (NO `reset_nickname`; gateway-local copy).
+  - The gateway's `ModerationActionsDb` (`src/modules/message-capture/moderationActionsDb.ts`) imports from `schema.ts` (the authoritative one). The `messages.ts` copy appears UNUSED for DB ops — but WE MUST ADD NEW COLUMNS TO BOTH to avoid type drift, OR confirm the `messages.ts` copy is dead and delete it. **Decision: add columns to `schema.ts` (authoritative) AND the `messages.ts` copy to keep `$inferInsert`/`$inferSelect` in sync (the gateway `ModerationAction` type flows from shared).** Verify with grep that `messages.ts` `pgModerationActionsTable` is not used by any `.insert()`/`.select()` at runtime before relying on it; if only re-exported, we still patch it for type-safety.
+- Migration mechanism: Drizzle-managed via `drizzle/migrations/*.sql` (journal `_journal.json`) applied by `runMigrations()` → `migratePostgres`. **New tables/columns must be added with `drizzle-kit generate` to produce a numbered `.sql` + journal entry**, OR (simpler, matches `0013_rename_*.sql` manual style) write a raw idempotent `.sql` under `drizzle/migrations/` AND register it in `_journal.json`. **Preferred here: use `pnpm drizzle-kit generate` so the journal stays consistent.** The legacy `src/shared/database/migrations/001_drop_unused_ai_columns.sql` is a PRE-drizzle manual script — do NOT follow that pattern.
+- **Historical lesson (MUST respect):** a prior migration (`0004_drop_unused_ai_columns.sql` = old `001_drop`) DELETED `ai_evidence`, `ai_policy_version`, `ai_moderation_raw` from `messages` with the note "written but never read". → Our new `moderation_actions` columns MUST be read (serializer + FE render). No write-only columns.
+- Embedding client: `embedText(text)` / `embedTexts(texts[])` in `src/modules/ai-moderation/embeddingClient.ts`. Returns `null` if `AI_LLM_EMBEDDING_MODEL` not configured. Reuses `config.AI_LLM_BASE_URL` + `config.AI_LLM_API_KEY`. OpenAI SDK v6 → `encoding_format: "float"` REQUIRED (Nvidia rejects base64).
+- Qdrant client: `src/modules/ai-moderation/qdrantClient.ts`. Has `ensureQdrantCollection(vectorSize)`, `upsertQdrantPoint(cacheKey, vector, payload)`, `searchQdrant(vector, limit, scoreThreshold)`. These are hardcoded to the cache collection name `config.QDRANT_COLLECTION ?? "gmw_text_moderation"`. **#3 needs a second collection** → generalize the client to accept a collection name param (add `ensureQdrantCollectionV2(name, size)` / `upsertQdrantPointV2(name, id, vector, payload)` / `searchQdrantV2(name, vector, limit, scoreThreshold)` OR refactor `collectionName()` to take an arg). Keep the cache path unchanged.
+- Capture hook: `captureMessage()` (`src/modules/message-capture/messageCapture.ts:201`) calls `messageStore.upsertMessageForCapture(messageRecord)` then (if not backlog) `queueMessageAnalysis`. **#3 embed must happen here**, async + fire-and-forget, after successful insert.
+- Public moderation view: `services/frontend/src/app/(dashboard)/moderation/view.tsx` renders `ActionRow` per action. The `ModerationAction` FE type is in `services/frontend/src/lib/types/moderation.ts` (NO new fields yet). The backend `moderationService.listActions` SQL is in `services/backend/src/modules/moderation/moderation.repository.ts:68` (raw SQL, selects fixed columns, joins `messages`).
+- oRPC wiring: `services/backend/src/orpc/router.ts` → `moderationRouter` (stats, actions) and `messagesRouter` (list, byChannel, getById, review, attachments). New procedures added here.
+
+---
+
+## TASK 1 — Schema: add explainability columns to `moderation_actions`
+
+**Objective:** Persist structured verdict on moderation actions so it can be surfaced (read) later.
+
+**Files:**
+- Modify: `services/discord-gateway/src/shared/database/schema.ts` (authoritative `pgModerationActionsTable`, ~line 638)
+- Modify: `services/discord-gateway/src/shared/database/schema/messages.ts` (`pgModerationActionsTable` copy, ~line 25) to keep type in sync
+- Create: `services/discord-gateway/drizzle/migrations/0015_add_moderation_explainability.sql`
+- Update: `services/discord-gateway/drizzle/migrations/meta/_journal.json` (add new entry)
+
+**Step 1: Add columns to both schema definitions**
+Add after `executed_at` in BOTH `pgModerationActionsTable` definitions:
+```ts
+    // ── Explainability (structured verdict, surfaced read-only to public web) ──
+    flags: pgText("flags"),            // JSON array of string flags, e.g. ["sara_agama","vulgar"]
+    categories: pgText("categories"), // JSON array of category strings
+    severity: pgText("severity", {
+      enum: ["none", "low", "medium", "high", "critical"],
+    }),
+    confidence: pgReal("confidence"),  // 0..1
+    score: pgReal("score"),            // 0..1 raw model score
+    evidence: pgText("evidence"),      // JSON array of short quoted snippets
+    policy_version: pgText("policy_version"), // rules.ts policy version string
+```
+Note: `flags`/`categories`/`evidence` stored as JSON-stringified TEXT (consistent with how `messages.ai_moderation_flags`/`ai_categories` are stored as TEXT elsewhere — confirm storage format in `updateMessageAIAnalysis`). Keep nullable.
+
+**Step 2: Generate/author the migration SQL**
+`0015_add_moderation_explainability.sql` (idempotent):
+```sql
+-- Add structured explainability columns to moderation_actions (read-only surfaced to public web).
+ALTER TABLE IF EXISTS "moderation_actions"
+  ADD COLUMN IF NOT EXISTS "flags" text,
+  ADD COLUMN IF NOT EXISTS "categories" text,
+  ADD COLUMN IF NOT EXISTS "severity" text
+    CHECK ("severity" IS NULL OR "severity" IN ('none','low','medium','high','critical')),
+  ADD COLUMN IF NOT EXISTS "confidence" real,
+  ADD COLUMN IF NOT EXISTS "score" real,
+  ADD COLUMN IF NOT EXISTS "evidence" text,
+  ADD COLUMN IF NOT EXISTS "policy_version" text;
+```
+Register in `_journal.json`: append an entry with `idx: 15`, a new unique `tag` (hash), `version`, `when` = Date.now(), `tag` short, `breakpoints: false`. Use `pnpm drizzle-kit generate` if possible to get a correct tag; otherwise hand-edit the journal carefully (copy an existing entry's shape).
+
+**Step 3: Type-check gateway**
+Run: `cd services/discord-gateway && pnpm typecheck`
+Expected: PASS (no new compile errors).
+
+**Step 4: Commit**
+```bash
+git add services/discord-gateway/src/shared/database/schema.ts \
+        services/discord-gateway/src/shared/database/schema/messages.ts \
+        services/discord-gateway/drizzle/migrations/0015_add_moderation_explainability.sql \
+        services/discord-gateway/drizzle/migrations/meta/_journal.json
+git commit -m "feat(db): add explainability columns to moderation_actions"
+```
+
+---
+
+## TASK 2 — Persist verdict at the auto-delete + command-handler call sites
+
+**Objective:** Populate the new columns from the already-computed `AnalysisResult` when a moderation action is logged. Fully automatic, no new behavior.
+
+**Files:**
+- Modify: `services/discord-gateway/src/modules/ai-moderation/autoDeleteManager.ts` (`logAutoDeleteAttempt` ~line 166, and the second `createModerationAction` call ~line 234 for nickname/mute paths)
+- Modify: `services/discord-gateway/src/modules/command-handler/moderation.handler.ts` (`createModerationAction` ~line 95)
+- Helper (create): `services/discord-gateway/src/modules/ai-moderation/verdictToActionFields.ts` — shared mapper so all 3 call sites stay DRY.
+
+**Step 1: Create the mapper helper**
+`verdictToActionFields.ts`:
+```ts
+import type { AnalysisResult } from "@/modules/ai-moderation/ai-analysis-worker";
+import type { ModerationActionInsert } from "@/shared/index"; // or inline shape
+
+/**
+ * Map a computed AI verdict into the explainability columns of a moderation
+ * action. Null-safe: missing fields stay null (e.g. manual admin actions have
+ * no AnalysisResult). This is read-only structured data — it does NOT change
+ * any enforcement decision.
+ */
+export function verdictToActionFields(result?: {
+  flags?: string[];
+  categories?: string[];
+  severity?: string;
+  confidence?: number;
+  score?: number;
+  evidence?: string[];
+  policyVersion?: string;
+}): {
+  flags: string | null;
+  categories: string | null;
+  severity: string | null;
+  confidence: number | null;
+  score: number | null;
+  evidence: string | null;
+  policy_version: string | null;
+} {
+  if (!result) {
+    return { flags: null, categories: null, severity: null, confidence: null,
+             score: null, evidence: null, policy_version: null };
+  }
+  const j = (v: unknown) => (v == null ? null : JSON.stringify(v));
+  return {
+    flags: j(result.flags),
+    categories: j(result.categories),
+    severity: result.severity ?? null,
+    confidence: result.confidence ?? null,
+    score: result.score ?? null,
+    evidence: j(result.evidence),
+    policy_version: result.policyVersion ?? null,
+  };
+}
+```
+
+**Step 2: Wire `logAutoDeleteAttempt`**
+Find the `createModerationAction({...})` in `logAutoDeleteAttempt` and spread the verdict fields:
+```ts
+await messageStore.createModerationAction({
+  message_id: message.id,
+  user_id: message.user_id,
+  guild_id: message.guild_id,
+  action_type: "delete_message",
+  reason: result.reason,
+  ...verdictToActionFields(result.analysisResult), // <-- pass the AnalysisResult through
+  executed_by: "auto-delete-manager",
+  status: ...,
+});
+```
+**IMPORTANT:** `result` here is `AutoDeleteResult` — verify it carries the `AnalysisResult` (or the verdict). If `AutoDeleteResult` does NOT carry the full `AnalysisResult`, trace where `attemptAutoDeleteFlaggedMessage` is called from and pass the `AnalysisResult` down (it is available in the analysis worker that triggered the delete). Confirm by reading `AutoDeleteResult` type + its producer. If the verdict is only available at the orchestrator level, add an optional `verdict?: AnalysisResult` field to `AutoDeleteResult` and populate it at the call site.
+
+**Step 3: Wire the second call site in `autoDeleteManager.ts`** (the mute/nickname path ~line 234) similarly, if it has an `AnalysisResult` available; otherwise leave fields null (manual-style action).
+
+**Step 4: Wire `moderation.handler.ts`** command path (~line 95) — pass `verdictToActionFields(verdict)` if the command handler has the `AnalysisResult` for the target message; otherwise nulls. Confirm what the handler receives.
+
+**Step 5: Type-check + lint**
+Run: `cd services/discord-gateway && pnpm typecheck && pnpm lint`
+Expected: PASS.
+
+**Step 6: Commit**
+```bash
+git add services/discord-gateway/src/modules/ai-moderation/verdictToActionFields.ts \
+        services/discord-gateway/src/modules/ai-moderation/autoDeleteManager.ts \
+        services/discord-gateway/src/modules/command-handler/moderation.handler.ts
+git commit -m "feat(mods): persist structured verdict into moderation_actions"
+```
+
+---
+
+## TASK 3 — Backend: surface explainability in `moderation.actions`
+
+**Objective:** Read the new columns in the public oRPC so the frontend can render them. (Read path — satisfies the "never write-only" rule.)
+
+**Files:**
+- Modify: `services/backend/src/modules/moderation/moderation.repository.ts` (`listActions` raw SQL ~line 68) — add new columns to SELECT + map.
+- Modify: `services/frontend/src/lib/types/moderation.ts` (`ModerationAction` interface) — add new fields.
+- Modify: `services/frontend/src/app/(dashboard)/moderation/view.tsx` (`ActionRow`) — render flags/categories badges + severity + confidence + evidence snippet.
+
+**Step 1: Extend backend SELECT**
+In `listActions`, add to the SELECT list: `a.flags, a.categories, a.severity, a.confidence, a.score, a.evidence, a.policy_version`. In the `.map(...)` add:
+```ts
+flags: r.flags ? safeJsonArray(String(r.flags)) : null,
+categories: r.categories ? safeJsonArray(String(r.categories)) : null,
+severity: r.severity ? String(r.severity) : null,
+confidence: r.confidence != null ? Number(r.confidence) : null,
+score: r.score != null ? Number(r.score) : null,
+evidence: r.evidence ? safeJsonArray(String(r.evidence)) : null,
+policy_version: r.policy_version ? String(r.policy_version) : null,
+```
+where `safeJsonArray(s)` = `JSON.parse(s)` wrapped in try/catch returning `[]` on failure (define a tiny local helper in the repository file).
+
+**Step 2: Extend FE type**
+In `services/frontend/src/lib/types/moderation.ts` `ModerationAction`:
+```ts
+  flags: string[] | null;
+  categories: string[] | null;
+  severity: "none" | "low" | "medium" | "high" | "critical" | null;
+  confidence: number | null;
+  score: number | null;
+  evidence: string[] | null;
+  policy_version: string | null;
+```
+
+**Step 3: Render in `ActionRow`**
+After the existing reason block, add (using existing `Badge` + `aiTone` from `@/lib/ai-status`):
+```tsx
+{a.severity && (
+  <Badge tone={aiTone(a.severity === "none" ? "clean" : a.severity)}>
+    {a.severity}
+  </Badge>
+)}
+{a.flags?.length ? (
+  <div className="mt-1 flex flex-wrap gap-1">
+    {a.flags.map((f) => <Badge key={f} tone="amber">{f}</Badge>)}
+  </div>
+) : null}
+{a.evidence?.length ? (
+  <div className="mt-1 text-xs text-ink-faint border-l-2 border-hairline pl-2">
+    “{a.evidence[0]}”
+  </div>
+) : null}
+{a.confidence != null && (
+  <div className="mono mt-0.5 text-[0.6rem] text-ink-faint">
+    conf {(a.confidence * 100).toFixed(0)}%
+  </div>
+)}
+```
+Keep `ActionRow` read-only. No admin controls.
+
+**Step 4: Type-check both services**
+Run: `cd services/backend && pnpm typecheck && pnpm lint` and `cd services/frontend && pnpm typecheck && pnpm lint`
+Expected: PASS.
+
+**Step 5: Commit**
+```bash
+git add services/backend/src/modules/moderation/moderation.repository.ts \
+        services/frontend/src/lib/types/moderation.ts \
+        services/frontend/src/app/\(dashboard\)/moderation/view.tsx
+git commit -m "feat(web): surface moderation explainability (flags/severity/evidence)"
+```
+
+---
+
+## TASK 4 — Qdrant client: support a second persistent collection
+
+**Objective:** Generalize the Qdrant client so #3 can use a dedicated archive collection without disturbing the automod cache.
+
+**Files:**
+- Modify: `services/discord-gateway/src/modules/ai-moderation/qdrantClient.ts`
+
+**Step 1: Add collection-aware variants**
+Refactor `collectionName()` to accept an optional name, and add V2 functions that take an explicit collection:
+```ts
+function collectionName(fallback = config.QDRANT_COLLECTION ?? "gmw_text_moderation"): string {
+  return fallback;
+}
+export const ARCHIVE_COLLECTION = config.QDRANT_ARCHIVE_COLLECTION ?? "gmw_message_archive";
+
+export async function ensureQdrantCollectionV2(name: string, vectorSize: number): Promise<boolean> {
+  // same body as ensureQdrantCollection but uses `name` instead of collectionName()
+}
+export async function upsertQdrantPointV2(
+  name: string, pointId: number, vector: number[], payload: QdrantVerdictPayload,
+): Promise<boolean> { /* PUT /collections/{name}/points with wait:true */ }
+export async function searchQdrantV2(
+  name: string, vector: number[], limit: number, scoreThreshold: number,
+): Promise<QdrantSearchHit[]> { /* POST /collections/{name}/points/search */ }
+```
+Keep all existing `ensureQdrantCollection` / `upsertQdrantPoint` / `searchQdrant` UNCHANGED (cache path). V2 functions mirror them with the `name` param. Reuse `request()` and the existing payload/score types.
+
+**Step 2: Type-check**
+Run: `cd services/discord-gateway && pnpm typecheck`
+Expected: PASS.
+
+**Step 3: Commit**
+```bash
+git add services/discord-gateway/src/modules/ai-moderation/qdrantClient.ts
+git commit -m "feat(qdrant): add collection-aware V2 upsert/search for archive"
+```
+
+---
+
+## TASK 5 — Capture-time embed + archive upsert
+
+**Objective:** Make every (non-backlog, text) captured message searchable in the persistent archive. Non-blocking / best-effort.
+
+**Files:**
+- Modify: `services/discord-gateway/src/modules/message-capture/messageCapture.ts` (`captureMessage` ~line 201)
+- Create: `services/discord-gateway/src/modules/message-capture/archiveEmbedder.ts` — wraps embed + upsert with fire-and-forget + rate-limit guard.
+
+**Step 1: Create `archiveEmbedder.ts`**
+```ts
+import { createChildLogger } from "@/shared/logger/index";
+import { embedText } from "@/modules/ai-moderation/embeddingClient";
+import { ARCHIVE_COLLECTION, ensureQdrantCollectionV2, upsertQdrantPointV2, qdrantPointId } from "@/modules/ai-moderation/qdrantClient";
+import { config } from "@/shared/config/config";
+
+const log = createChildLogger("archive-embedder");
+
+/**
+ * Fire-and-forget: embed a captured message and upsert into the persistent
+ * archive collection. Failures are swallowed — searching is a nice-to-have,
+ * never a precondition for capture or moderation.
+ */
+export function archiveMessageEmbedded(message: {
+  id: string; content: string; username: string; channel_id: string; guild_id: string; created_at: number;
+}): void {
+  if (!config.AI_LLM_EMBEDDING_MODEL) return; // embeddings disabled → skip
+  if (!message.content || message.content.trim().length < 3) return;
+  void (async () => {
+    try {
+      const vector = await embedText(message.content);
+      if (!vector) return;
+      const ok = await ensureQdrantCollectionV2(ARCHIVE_COLLECTION, vector.length);
+      if (!ok) return;
+      await upsertQdrantPointV2(ARCHIVE_COLLECTION, qdrantPointId(`archive:${message.id}`), vector, {
+        text: message.content.slice(0, 4000),
+        flags: "", // not a verdict payload; keep shape compatible
+        analyzed_at: Date.now(),
+        expires_at: Date.now() + 1000 * 60 * 60 * 24 * 365 * 5, // 5y persistent
+        content_hash: undefined,
+      });
+    } catch (err) {
+      log.debug({ messageId: message.id, error: err instanceof Error ? err.message : String(err) }, "archive embed skipped");
+    }
+  })();
+}
+```
+Payload type reuse: `QdrantVerdictPayload` has `text`, `flags`, `analyzed_at`, `expires_at`, `content_hash?`. For the archive we only need `text` + timestamps; set `flags: ""` (empty, ignored by search filter which keys on `expires_at`). **Acceptable:** the search path filters `expires_at >= now` — 5y window satisfies that.
+
+**Step 2: Call from `captureMessage`**
+In `captureMessage`, after `const inserted = await messageStore.upsertMessageForCapture(messageRecord); if (!inserted) return;` and BEFORE the backlog branch, add:
+```ts
+if (!isBacklog && messageRecord.content) {
+  archiveMessageEmbedded(messageRecord);
+}
+```
+(`messageRecord` is the `MessageRecord` from `buildMessageRecord`; confirm it carries `content`, `channel_id`, `guild_id`, `created_at`. It does — see `messagesCrud`/`types`.)
+
+**Step 3: Type-check + lint**
+Run: `cd services/discord-gateway && pnpm typecheck && pnpm lint`
+Expected: PASS.
+
+**Step 4: Commit**
+```bash
+git add services/discord-gateway/src/modules/message-capture/archiveEmbedder.ts \
+        services/discord-gateway/src/modules/message-capture/messageCapture.ts
+git commit -m "feat(archive): embed captured messages into persistent Qdrant archive"
+```
+
+---
+
+## TASK 6 — Backend: `messages.semanticSearch` oRPC
+
+**Objective:** Public, read-only semantic search over the message archive.
+
+**Files:**
+- Modify: `services/backend/src/modules/messages/messages.repository.ts` — add `semanticSearch(query, limit, guildId?)`.
+- Modify: `services/backend/src/modules/messages/messages.service.ts` — expose `semanticSearch`.
+- Modify: `services/backend/src/orpc/router.ts` — add `messages.semanticSearch` procedure.
+- Create (or reuse): an embedding call from the backend. The backend does NOT import the gateway's `embeddingClient`. **Decision:** add a minimal backend embed helper `services/backend/src/modules/messages/embed.ts` that calls the same OpenAI-compatible endpoint via `config` (reuse `config.AI_LLM_BASE_URL`/`AI_LLM_API_KEY`/`AI_LLM_EMBEDDING_MODEL` if present on the backend; if not configured, return a clear "search unavailable" error). Mirror `encoding_format: "float"`.
+- Modify: `services/backend/src/modules/messages/messages.schema.ts` — add `semanticSearchQuery` zod schema (limit, guildId?, query).
+
+**Step 1: Backend embed helper** (`embed.ts`)
+```ts
+import OpenAI from "openai";
+import { config } from "@/shared/config/index";
+import { createChildLogger } from "@/shared/logger/index";
+const log = createChildLogger("messages-embed");
+let client: OpenAI | null = null;
+function getClient() {
+  if (!config.AI_LLM_API_KEY || !config.AI_LLM_EMBEDDING_MODEL) return null;
+  if (!client) client = new OpenAI({ apiKey: config.AI_LLM_API_KEY, baseURL: config.AI_LLM_BASE_URL, maxRetries: 0, timeout: 30_000 });
+  return client;
+}
+export async function embedQuery(text: string): Promise<number[] | null> {
+  const c = getClient(); if (!c) return null;
+  try {
+    const r = await c.embeddings.create({ model: config.AI_LLM_EMBEDDING_MODEL as string, input: text, encoding_format: "float" });
+    return r.data[0].embedding;
+  } catch (e) { log.warn({ error: e instanceof Error ? e.message : String(e) }, "query embed failed"); return null; }
+}
+```
+
+**Step 2: Repository `semanticSearch`**
+```ts
+async semanticSearch(queryVector: number[], limit: number, guildId?: string) {
+  // Search archive collection, then join messages for text + channel.
+  const hits = await searchQdrantV2(ARCHIVE_COLLECTION, queryVector, limit, 0.6);
+  const ids = hits.map(h => h.cacheKey.replace("qdrant:", "")); // point id → we stored archive:<messageId>
+  // decode: qdrantPointId is a uint64; we need the original message id.
+  // SIMPLER: store message_id inside the payload too. → update archiveEmbedder payload to include `message_id`.
+  ...
+}
+```
+**REFINEMENT (important):** `qdrantPointId` is a hash, not reversible. So the archive payload MUST carry `message_id` (and `channel_id`, `guild_id`, `username`, `created_at`) so the backend can return full results without a reverse lookup. **Update `archiveEmbedder.ts` payload** to include those fields, and relax `QdrantVerdictPayload` (or create `QdrantArchivePayload`) to allow them. Then `semanticSearch` returns the payloads directly (already contain text + metadata) — no DB join needed, and it works even for deleted messages (archive keeps the text). Apply `guildId` filter client-side on the returned payloads.
+
+**Step 3: Service + router**
+`messages.service.ts`: `async semanticSearch(query: string, limit: number, guildId?: string)` → embed → `repository.semanticSearch`.
+`orpc/router.ts` under `messagesRouter`:
+```ts
+semanticSearch: os
+  .input(z.object({ query: z.string().min(1), limit: z.coerce.number().int().positive().max(50).default(10), guildId: z.string().optional() }))
+  .handler(async ({ input }) => {
+    const results = await messagesService.semanticSearch(input.query, input.limit, input.guildId);
+    return { results, nextCursor: null };
+  }),
+```
+
+**Step 4: Type-check + lint (backend)**
+Run: `cd services/backend && pnpm typecheck && pnpm lint`
+Expected: PASS.
+
+**Step 5: Commit**
+```bash
+git add services/backend/src/modules/messages/embed.ts \
+        services/backend/src/modules/messages/messages.repository.ts \
+        services/backend/src/modules/messages/messages.service.ts \
+        services/backend/src/modules/messages/messages.schema.ts \
+        services/backend/src/orpc/router.ts
+git commit -m "feat(api): public semantic message search over archive"
+```
+
+---
+
+## TASK 7 — Frontend: semantic search UI on `messages` view
+
+**Objective:** Public, read-only search box + results on the existing messages dashboard.
+
+**Files:**
+- Modify: `services/frontend/src/app/(dashboard)/messages/page.tsx` + `view.tsx` — add a search input (debounced) that calls a new `useMessagesSemanticSearch` hook → `messages.semanticSearch` oRPC, renders results as message cards (reuse `GlassPanel`/`Badge`/existing message row components).
+- Modify: `services/frontend/src/lib/types/message.ts` — add `SemanticSearchResult` + `SemanticSearchResponse` types.
+- Modify: `services/frontend/src/lib/api/client.ts` (or `server.ts`) — add `semanticSearch` fetcher/routers export if using oRPC client; if the FE uses raw fetch through the proxy, add a `POST /api/messages/semantic-search` or an oRPC client call consistent with existing `messages.*` calls (follow the EXISTING pattern in `src/lib/api/` — inspect how `messages.list` is called and replicate).
+
+**Step 1: Add FE types**
+```ts
+export interface SemanticSearchResult {
+  message_id: string;
+  content: string;
+  username: string;
+  channel_id: string;
+  guild_id: string;
+  created_at: number;
+  score: number;
+}
+export interface SemanticSearchResponse { results: SemanticSearchResult[]; nextCursor: string | null; }
+```
+
+**Step 2: Add hook + wire view**
+Follow the existing `use-moderation.ts` SWR pattern. Add `useMessagesSemanticSearch(query, guildId?)` returning `{ data, isLoading, error }`. In `messages/view.tsx`, add a search `Input` (from `@/components/primitives`) at the top, debounce ~300ms, and render results below the live list when a query is present. Reuse the message-row rendering already in that view (do not invent a new component).
+
+**Step 3: Type-check + lint (frontend)**
+Run: `cd services/frontend && pnpm typecheck && pnpm lint`
+Expected: PASS.
+
+**Step 4: Commit**
+```bash
+git add services/frontend/src/app/\(dashboard\)/messages/ \
+        services/frontend/src/lib/types/message.ts \
+        services/frontend/src/lib/api/ \
+        services/frontend/src/hooks/
+git commit -m "feat(web): public semantic message search UI"
+```
+
+---
+
+## TASK 8 — Build all services + deploy + verify
+
+1. `cd services/discord-gateway && pnpm typecheck && pnpm build && pnpm lint`
+2. `cd services/backend && pnpm typecheck && pnpm build && pnpm lint`
+3. `cd services/frontend && pnpm typecheck && pnpm build && pnpm lint`
+4. Commit any formatting fixes (biome `--unsafe` if import order), author `asepharyana`, NO Co-Authored-By.
+5. `git push origin main` → watch `gh run watch` on "Build & Deploy (Nix)".
+6. After deploy: verify `systemctl show gmw-discord-gateway.service --property=ActiveEnterTimestamp,SubState` reflects new timestamp; same for backend + frontend.
+7. Smoke: `curl -s http://127.0.0.1:4001/trpc/messages.semanticSearch?input=<urlencoded json>` OR via the public web `imphnen.asepharyana.my.id` messages page → type a query → expect results (after some messages have been embedded; embeddings only run on NEW captures post-deploy, so seed a few test messages or backfill).
+8. Moderation explainability: trigger/observe a flagged message → confirm `moderation_actions.flags` is populated (SQL `SELECT flags, severity FROM moderation_actions ORDER BY created_at DESC LIMIT 5;`) and the public moderation view shows badges.
+
+---
+
+## RISKS / TRADEOFFS / OPEN QUESTIONS
+- **Embedding cost:** #3 embeds EVERY captured message → more embedding API calls. Mitigated: only text ≥3 chars, fire-and-forget, skip if model unconfigured. If cost is a concern, batch embed (reuse `embedTexts`) per capture burst — but start simple (per-message) and observe.
+- **Backfill:** post-deploy, the archive is empty until new messages arrive. Optional follow-up: a one-off backfill script over existing `messages` (out of scope for this plan unless user asks).
+- **Schema duplication:** the `pgModerationActionsTable` double-definition must stay in sync (Task 1 patches both). If `messages.ts` copy is provably dead, a follow-up can delete it — but NOT in this plan (avoid scope creep / risk).
+- **`AutoDeleteResult` verdict availability (Task 2):** requires confirming the `AnalysisResult` is reachable at the `createModerationAction` call sites. If not, we add an optional field to `AutoDeleteResult` at the orchestrator call site. This is the highest-risk integration point — verify before assuming.
+- **Public exposure:** semantic search returns message text + usernames. This is INTENDED (web is public for users). No auth added. If a guild wants private, that is a future config (out of scope).
+- **Qdrant payload type:** reusing `QdrantVerdictPayload` for archive is slightly awkward (carries `flags`/`expires_at` semantics). Cleaner: introduce `QdrantArchivePayload` with `message_id`, `channel_id`, `guild_id`, `username`, `content`, `created_at`, `expires_at`. **Prefer the dedicated payload type in Task 4/5** to avoid confusion.
+
+## VERIFICATION CHECKLIST
+- [ ] `moderation_actions` has 7 new columns (DB + both schema defs).
+- [ ] A real auto-delete populates `flags`/`severity`/`evidence` (verified via SQL).
+- [ ] Public moderation view renders badges + evidence (manual browser check on imphnen.asepharyana.my.id/moderation).
+- [ ] New message capture upserts a point into `gmw_message_archive` (verify via Qdrant `/collections/gmw_message_archive/points/count`).
+- [ ] `messages.semanticSearch` returns relevant results for a known phrase.
+- [ ] All three services: typecheck + build + lint green; CI "Build & Deploy (Nix)" green; systemd timestamps updated.
@@ -0,0 +1,43 @@
+import { config } from "@/shared/config/index.js";
+import { createChildLogger } from "@/shared/logger/index.js";
+
+const logger = createChildLogger("messages-embed");
+
+/**
+ * Embed a search query with the configured OpenAI-compatible embedding model.
+ * Uses raw fetch (the backend has no openai SDK dependency) and returns null
+ * when embeddings are not configured (search unavailable).
+ *
+ * encoding_format: "float" is REQUIRED — Nvidia-backed models reject base64.
+ */
+export async function embedQuery(text: string): Promise<number[] | null> {
+  if (!config.AI_LLM_API_KEY || !config.AI_LLM_EMBEDDING_MODEL) return null;
+  try {
+    const res = await fetch(`${config.AI_LLM_BASE_URL}/embeddings`, {
+      method: "POST",
+      headers: {
+        "Content-Type": "application/json",
+        Authorization: `Bearer ${config.AI_LLM_API_KEY}`,
+      },
+      body: JSON.stringify({
+        model: config.AI_LLM_EMBEDDING_MODEL,
+        input: text,
+        encoding_format: "float",
+      }),
+    });
+    if (!res.ok) {
+      logger.warn({ status: res.status }, "query embed HTTP error");
+      return null;
+    }
+    const json = (await res.json()) as {
+      data?: Array<{ embedding?: number[] }>;
+    };
+    return json.data?.[0]?.embedding ?? null;
+  } catch (error) {
+    logger.warn(
+      { error: error instanceof Error ? error.message : String(error) },
+      "query embed failed",
+    );
+    return null;
+  }
+}
@@ -41,3 +41,11 @@ export const messageUpdateSchema = z.object({
 export type MessageQuery = z.infer<typeof messageQuerySchema>;
 export type MessageCreate = z.infer<typeof messageCreateSchema>;
 export type MessageUpdate = z.infer<typeof messageUpdateSchema>;
+
+export const semanticSearchSchema = z.object({
+  query: z.string().min(1).max(500),
+  limit: z.coerce.number().int().positive().max(50).default(10),
+  guildId: z.string().optional(),
+});
+
+export type SemanticSearchQuery = z.infer<typeof semanticSearchSchema>;
@@ -1,7 +1,9 @@
 import { NotFoundError, ValidationError } from "@/shared/errors/index";
 import { createChildLogger } from "@/shared/logger/index";
+import { embedQuery } from "./embed.js";
 import { messagesRepository } from "./messages.repository.js";
-import type { MessageQuery } from "./messages.schema.js";
+import type { MessageQuery, SemanticSearchQuery } from "./messages.schema.js";
+import { searchArchive } from "./qdrant.js";

 const logger = createChildLogger("messages.service");

@@ -78,6 +80,40 @@ export class MessagesService {
    logger.debug({ channelId, limit }, "Getting review messages");
    return messagesRepository.getReviewMessages(channelId, limit);
  }
+
+  /**
+   * Public, read-only semantic search over the persistent message archive.
+   * Embeds the query, searches Qdrant, returns text + metadata. Best-effort:
+   * if embeddings/Qdrant are unavailable, returns an empty result set.
+   */
+  async semanticSearch(
+    input: SemanticSearchQuery,
+  ): Promise<{ results: ReturnType<typeof mapSearchHit>[]; nextCursor: null }> {
+    const vector = await embedQuery(input.query);
+    if (!vector) {
+      logger.debug(
+        { query: input.query },
+        "semantic search skipped: no embedder",
+      );
+      return { results: [], nextCursor: null };
+    }
+    const hits = await searchArchive(vector, input.limit, 0.6);
+    const results = hits.map((h) => mapSearchHit(h));
+    return { results, nextCursor: null };
+  }
+}
+
+/** Shape returned to the frontend (text + metadata from the archive payload). */
+function mapSearchHit(hit: {
+  score: number;
+  payload: { text: string; content_hash?: string; analyzed_at: number };
+}) {
+  return {
+    message_id: hit.payload.content_hash ?? null,
+    content: hit.payload.text,
+    score: hit.score,
+    created_at: hit.payload.analyzed_at,
+  };
 }

 export const messagesService = new MessagesService();
@@ -0,0 +1,95 @@
+import { config } from "@/shared/config/index.js";
+import { createChildLogger } from "@/shared/logger/index.js";
+
+const logger = createChildLogger("messages-qdrant");
+
+export interface ArchiveHit {
+  score: number;
+  payload: {
+    text: string;
+    content_hash?: string;
+    analyzed_at: number;
+    expires_at: number;
+  };
+}
+
+function baseUrl(): string {
+  return (config.QDRANT_URL ?? "http://100.121.180.82:6333").replace(
+    /\/+$/,
+    "",
+  );
+}
+
+function headers(): Record<string, string> {
+  const h: Record<string, string> = { "Content-Type": "application/json" };
+  if (config.QDRANT_API_KEY) h["api-key"] = config.QDRANT_API_KEY;
+  return h;
+}
+
+export const ARCHIVE_COLLECTION =
+  config.QDRANT_ARCHIVE_COLLECTION ?? "gmw_message_archive";
+
+async function request(
+  method: string,
+  path: string,
+  body?: unknown,
+  timeoutMs = 10_000,
+): Promise<unknown> {
+  const controller = new AbortController();
+  const timer = setTimeout(() => controller.abort(), timeoutMs);
+  try {
+    const res = await fetch(`${baseUrl()}${path}`, {
+      method,
+      headers: headers(),
+      body: body === undefined ? undefined : JSON.stringify(body),
+      signal: controller.signal,
+    });
+    const text = await res.text();
+    if (!res.ok) {
+      throw new Error(
+        `Qdrant ${method} ${path} -> ${res.status}: ${text.slice(0, 200)}`,
+      );
+    }
+    return text ? JSON.parse(text) : null;
+  } finally {
+    clearTimeout(timer);
+  }
+}
+
+/** Search the archive collection for the nearest vectors to `vector`. */
+export async function searchArchive(
+  vector: number[],
+  limit: number,
+  scoreThreshold: number,
+): Promise<ArchiveHit[]> {
+  if (!config.QDRANT_URL) return [];
+  try {
+    const json = (await request(
+      "POST",
+      `/collections/${ARCHIVE_COLLECTION}/points/search`,
+      {
+        vector,
+        limit,
+        score_threshold: scoreThreshold,
+        with_payload: true,
+      },
+    )) as {
+      result?: Array<{
+        score?: number;
+        payload?: ArchiveHit["payload"];
+      }>;
+    };
+    return (json.result ?? [])
+      .filter((h) => h.payload?.text)
+      .map((h) => ({
+        score: h.score ?? 0,
+        payload: h.payload as ArchiveHit["payload"],
+      }));
+  } catch (error) {
+    logger.warn(
+      { error: error instanceof Error ? error.message : String(error) },
+      "archive search failed",
+    );
+    return [];
+  }
+}
@@ -17,6 +17,20 @@ const ACTION_TYPES = [
 ] as const;
 const STATUSES = ["pending", "executed", "failed"] as const;

+/** Parse a JSON-stringified array column (e.g. flags/categories/evidence).
+ *  Returns null on empty/malformed input so the FE can treat it as "no data". */
+function parseJsonArray(value: unknown): string[] | null {
+  if (value == null) return null;
+  const str = typeof value === "string" ? value : String(value);
+  if (str.length === 0) return null;
+  try {
+    const parsed = JSON.parse(str);
+    return Array.isArray(parsed) ? (parsed as string[]) : null;
+  } catch {
+    return null;
+  }
+}
+
 export class ModerationRepository {
  async getStats() {
    const db = getDatabase();
@@ -103,6 +117,13 @@ export class ModerationRepository {
        a.error,
        a.created_at,
        a.executed_at,
+        a.flags,
+        a.categories,
+        a.severity,
+        a.confidence,
+        a.score,
+        a.evidence,
+        a.policy_version,
        m.username,
        LEFT(m.content, 300) AS content
      FROM moderation_actions a
@@ -126,6 +147,13 @@ export class ModerationRepository {
      error: r.error ? String(r.error) : null,
      created_at: r.created_at ? Number(r.created_at) : null,
      executed_at: r.executed_at ? Number(r.executed_at) : null,
+      flags: parseJsonArray(r.flags),
+      categories: parseJsonArray(r.categories),
+      severity: r.severity ? String(r.severity) : null,
+      confidence: r.confidence != null ? Number(r.confidence) : null,
+      score: r.score != null ? Number(r.score) : null,
+      evidence: parseJsonArray(r.evidence),
+      policy_version: r.policy_version ? String(r.policy_version) : null,
      username: r.username ? String(r.username) : null,
      content: r.content ? String(r.content) : null,
    }));
@@ -16,7 +16,10 @@ import {
  skip,
  stop,
 } from "../modules/media/media.service";
-import { messageQuerySchema } from "../modules/messages/messages.schema";
+import {
+  messageQuerySchema,
+  semanticSearchSchema,
+} from "../modules/messages/messages.schema";
 import { messagesService } from "../modules/messages/messages.service";
 import { moderationService } from "../modules/moderation/moderation.service";
 import { recordingsService } from "../modules/recordings/recordings.service";
@@ -136,6 +139,10 @@ const messagesRouter = {
      );
      return { results: rows, limit: input.limit, cursor: null };
    }),
+  // Public, read-only semantic search over the message archive.
+  semanticSearch: os
+    .input(semanticSearchSchema)
+    .handler(({ input }) => messagesService.semanticSearch(input)),
 };

 // ── Moderation ───────────────────────────────────────────────────
@@ -134,6 +134,7 @@ export const configSchema = z
      .default("https://9router.asepharyana.my.id/v1"),
    AI_LLM_MODEL: z.string().default("text"),
    AI_LLM_VISION_MODEL: z.string().optional(),
+    AI_LLM_EMBEDDING_MODEL: z.string().optional(),
    AI_LLM_MAX_CONCURRENT: z.coerce.number().int().positive().default(5),
    AI_LLM_IMAGE_MAX_DIMENSION: z.coerce
      .number()
@@ -208,6 +209,11 @@ export const configSchema = z
      .default("https://api.openai.com/v1"),
    OPENAI_MODERATION_MODEL: z.string().default("omni-moderation-latest"),

+    // ── Qdrant (message archive for semantic search) ──────────────────
+    QDRANT_URL: z.string().optional(),
+    QDRANT_API_KEY: z.string().optional(),
+    QDRANT_ARCHIVE_COLLECTION: z.string().default("gmw_message_archive"),
+
    // ── Auto Delete ─────────────────────────────────────────────────────
    AUTO_DELETE_FLAGGED_ENABLED: z
      .string()
@@ -0,0 +1,16 @@
+-- Migration: 0015_add_moderation_explainability.sql
+-- Date: 2026-08-18
+-- Description: Add structured explainability columns to moderation_actions.
+-- These are READ (surfaced read-only to the public web) so they are never
+-- "written but never read" — they back the public moderation transparency view.
+-- Idempotent: no-ops on databases that already carry the columns.
+
+ALTER TABLE IF EXISTS "moderation_actions"
+  ADD COLUMN IF NOT EXISTS "flags" text,
+  ADD COLUMN IF NOT EXISTS "categories" text,
+  ADD COLUMN IF NOT EXISTS "severity" text
+    CHECK ("severity" IS NULL OR "severity" IN ('none','low','medium','high','critical')),
+  ADD COLUMN IF NOT EXISTS "confidence" real,
+  ADD COLUMN IF NOT EXISTS "score" real,
+  ADD COLUMN IF NOT EXISTS "evidence" text,
+  ADD COLUMN IF NOT EXISTS "policy_version" text;
@@ -106,6 +106,13 @@
      "when": 1785621600000,
      "tag": "0014_add_term_glossary_cache",
      "breakpoints": true
+    },
+    {
+      "idx": 15,
+      "version": "7",
+      "when": 1787184000000,
+      "tag": "0015_add_moderation_explainability",
+      "breakpoints": true
    }
  ]
 }
@@ -10,6 +10,7 @@ import {
 } from "./autoDeleteEligibility.js";
 import { logDeletionToChannel } from "./autoDeleteLogger.js";
 import { sendDeletionNotification } from "./autoDeleteNotify.js";
+import { verdictToActionFields } from "./verdictToActionFields.js";

 const logger = createChildLogger("auto-delete-manager");

@@ -174,6 +175,7 @@ async function logAutoDeleteAttempt(
      guild_id: message.guild_id,
      action_type: "delete_message",
      reason: result.reason,
+      ...verdictToActionFields(message),
      executed_by: "auto-delete-manager",
      status: result.deleted
        ? "executed"
@@ -238,6 +240,7 @@ export async function attemptAutoDeleteFlaggedMessage(
            action_type: "reset_nickname",
            reason:
              "nickname melanggar aturan server (offensive_username); pesan dibiarkan",
+            ...verdictToActionFields(message),
            executed_by: "auto-delete-manager",
            status: resetOk ? "executed" : "failed",
            error: resetOk ? null : "nickname_reset_failed",
@@ -50,6 +50,10 @@ function collectionName(): string {
  return config.QDRANT_COLLECTION ?? "gmw_text_moderation";
 }

+/** Persistent archive collection for semantic message search (no TTL). */
+export const ARCHIVE_COLLECTION =
+  config.QDRANT_ARCHIVE_COLLECTION ?? "gmw_message_archive";
+
 function headers(): Record<string, string> {
  const h: Record<string, string> = {
    "Content-Type": "application/json",
@@ -390,3 +394,131 @@ export async function deleteQdrantPointsByContentHash(
 export function isQdrantConfigured(): boolean {
  return Boolean(config.QDRANT_URL);
 }
+
+// ─── Archive variants (collection-aware, for persistent message search) ───
+// These mirror the cache functions but take an explicit collection name so the
+// semantic-search archive (gmw_message_archive) can live alongside the
+// TTL-bounded automod cache without disturbing it.
+
+/** Ensure an arbitrary collection exists with the right vector size. */
+export async function ensureQdrantCollectionV2(
+  name: string,
+  vectorSize: number,
+): Promise<boolean> {
+  try {
+    let existing: {
+      result?: { config?: { params?: { vectors?: { size?: number } } } };
+    } | null = null;
+    try {
+      existing = (await request("GET", `/collections/${name}`)) as {
+        result?: { config?: { params?: { vectors?: { size?: number } } } };
+      } | null;
+    } catch (error) {
+      if (!(error instanceof Error) || !error.message.includes("-> 404")) {
+        throw error;
+      }
+    }
+
+    const size = existing?.result?.config?.params?.vectors?.size;
+    if (size === vectorSize) return true;
+
+    if (size !== undefined && size !== vectorSize) {
+      log.warn(
+        { collection: name, oldSize: size, newSize: vectorSize },
+        "Qdrant archive collection vector size changed — recreating collection",
+      );
+      await request("DELETE", `/collections/${name}`);
+    }
+
+    await request("PUT", `/collections/${name}`, {
+      vectors: { size: vectorSize, distance: "Cosine" },
+    });
+    return true;
+  } catch (error) {
+    log.error(
+      {
+        error: error instanceof Error ? error.message : String(error),
+        collection: name,
+      },
+      "Failed to ensure Qdrant archive collection",
+    );
+    return false;
+  }
+}
+
+/** Upsert one embedding + payload point into a named collection. */
+export async function upsertQdrantPointV2(
+  name: string,
+  pointId: number,
+  vector: number[],
+  payload: QdrantVerdictPayload,
+): Promise<boolean> {
+  try {
+    if (!(await ensureQdrantCollectionV2(name, vector.length))) return false;
+    await request(
+      "PUT",
+      `/collections/${name}/points`,
+      {
+        points: [{ id: pointId, vector, payload }],
+        wait: true,
+      },
+      30_000,
+    );
+    return true;
+  } catch (error) {
+    log.warn(
+      {
+        error: error instanceof Error ? error.message : String(error),
+        collection: name,
+      } as Record<string, unknown>,
+      "Qdrant archive upsert failed — entry skipped",
+    );
+    return false;
+  }
+}
+
+export interface QdrantArchiveHit {
+  pointId: number;
+  score: number;
+  payload: QdrantVerdictPayload;
+}
+
+/** Search a named collection for the nearest stored vector. */
+export async function searchQdrantV2(
+  name: string,
+  vector: number[],
+  limit: number,
+  scoreThreshold: number,
+): Promise<QdrantArchiveHit[]> {
+  try {
+    const json = (await request("POST", `/collections/${name}/points/search`, {
+      vector,
+      limit,
+      score_threshold: scoreThreshold,
+      with_payload: true,
+    })) as {
+      result?: Array<{
+        id?: number;
+        score?: number;
+        payload?: QdrantVerdictPayload;
+      }>;
+    };
+
+    return (json.result ?? [])
+      .filter((hit) => hit.payload?.text)
+      .map((hit) => ({
+        pointId: hit.id ?? 0,
+        score: hit.score ?? 0,
+        payload: hit.payload as QdrantVerdictPayload,
+      }));
+  } catch (error) {
+    log.warn(
+      {
+        error: error instanceof Error ? error.message : String(error),
+        collection: name,
+      } as Record<string, unknown>,
+      "Qdrant archive search failed — semantic search skipped",
+    );
+    return [];
+  }
+}
@@ -0,0 +1,48 @@
+import type { MessageRecord } from "../message-capture/types.js";
+
+/**
+ * Map a captured message's persisted AI verdict (the `ai_*` columns on
+ * MessageRecord) into the explainability columns of a moderation action.
+ *
+ * This is READ-ONLY structured data — it never changes any enforcement
+ * decision. It exists so the public web view can show *why* a message was
+ * moderated, making GMW's automod transparent instead of a black box.
+ *
+ * All fields are null-safe: manual actions (e.g. command-handler bans) carry
+ * no AI verdict, so they simply store nulls and the UI falls back to the
+ * free-text `reason`.
+ */
+export function verdictToActionFields(message?: MessageRecord | null): {
+  flags: string | null;
+  categories: string | null;
+  severity: string | null;
+  confidence: number | null;
+  score: number | null;
+  evidence: string | null;
+  policy_version: string | null;
+} {
+  if (!message) {
+    return {
+      flags: null,
+      categories: null,
+      severity: null,
+      confidence: null,
+      score: null,
+      evidence: null,
+      policy_version: null,
+    };
+  }
+
+  // ai_moderation_flags / ai_categories are stored as JSON-stringified TEXT
+  // (see messagesAnalysis.buildAIAnalysisSet → stringifyAIList). Pass them
+  // through verbatim so the backend can JSON.parse them back into arrays.
+  return {
+    flags: message.ai_moderation_flags ?? null,
+    categories: message.ai_categories ?? null,
+    severity: message.ai_severity ?? null,
+    confidence: message.ai_confidence ?? null,
+    score: message.ai_moderation_score ?? null,
+    evidence: null, // not persisted on MessageRecord; reserved for future use
+    policy_version: null, // set by caller if a policy version is available
+  };
+}
@@ -0,0 +1,63 @@
+import { embedText } from "@/modules/ai-moderation/embeddingClient.js";
+import {
+  ARCHIVE_COLLECTION,
+  qdrantPointId,
+  upsertQdrantPointV2,
+} from "@/modules/ai-moderation/qdrantClient.js";
+import { config } from "@/shared/config/config.js";
+import { createChildLogger } from "@/shared/logger/index";
+
+const log = createChildLogger("archive-embedder");
+
+export interface ArchiveMessage {
+  id: string;
+  content: string;
+  username: string;
+  channel_id: string;
+  guild_id: string;
+  created_at: number;
+}
+
+/**
+ * Fire-and-forget: embed a captured message and upsert it into the persistent
+ * archive collection so the public web can semantic-search the corpus.
+ *
+ * Failures are swallowed — searching is a nice-to-have, never a precondition
+ * for capture or moderation. The message text is kept in the payload so the
+ * search endpoint can return results even for deleted messages.
+ */
+export function archiveMessageEmbedded(message: ArchiveMessage): void {
+  if (!config.AI_LLM_EMBEDDING_MODEL) return; // embeddings disabled → skip
+  const text = message.content?.trim();
+  if (!text || text.length < 3) return;
+
+  void (async () => {
+    try {
+      const vector = await embedText(text);
+      if (!vector) return;
+      const ok = await upsertQdrantPointV2(
+        ARCHIVE_COLLECTION,
+        qdrantPointId(`archive:${message.id}`),
+        vector,
+        {
+          text: text.slice(0, 4000),
+          flags: "",
+          analyzed_at: Date.now(),
+          // 5-year persistent window (archive is NOT a TTL cache).
+          expires_at: Date.now() + 1000 * 60 * 60 * 24 * 365 * 5,
+          content_hash: message.id,
+        },
+      );
+      if (!ok) return;
+      log.debug({ messageId: message.id }, "Archived message embedding");
+    } catch (err) {
+      log.debug(
+        {
+          messageId: message.id,
+          error: err instanceof Error ? err.message : String(err),
+        },
+        "archive embed skipped",
+      );
+    }
+  })();
+}
@@ -4,6 +4,7 @@ import { config } from "../../shared/config/config.js";
 import { queueMessageAnalysis } from "../ai-moderation/aiAnalyzer.js";
 import { processAttachmentUpload } from "../attachment-upload/attachmentUploader.js";
 import type { EventBroadcaster } from "../event-broadcaster/eventBroadcaster.js";
+import { archiveMessageEmbedded } from "../message-capture/archiveEmbedder.js";
 import {
  getDisplayContent,
  getMessageLocation,
@@ -203,6 +204,7 @@ export async function captureMessage(
  type: "text" | "edited" | "deleted",
  options: { source?: "live" | "backlog" } = {},
 ): Promise<void> {
+  const isBacklog = options.source === "backlog";
  const location = getMessageLocation(message);
  const messageRecord = buildMessageRecord(message, type);

@@ -211,7 +213,11 @@ export async function captureMessage(
    return;
  }

-  const isBacklog = options.source === "backlog";
+  // Fire-and-forget: make the captured message searchable in the persistent
+  // archive (public semantic search). Never blocks capture/moderation.
+  if (!isBacklog && messageRecord.content) {
+    archiveMessageEmbedded(messageRecord);
+  }

  if (_eventBroadcaster && !isBacklog) {
    _eventBroadcaster.messageCreated(messageRecord);
@@ -178,6 +178,7 @@ export const configSchema = z
    // embedding column remains as a legacy fallback).
    QDRANT_URL: z.string().optional(),
    QDRANT_COLLECTION: z.string().default("gmw_text_moderation"),
+    QDRANT_ARCHIVE_COLLECTION: z.string().default("gmw_message_archive"),
    QDRANT_API_KEY: z.string().optional(),
    AI_LLM_MAX_CONCURRENT: z.coerce.number().int().positive().default(8),
    AI_LLM_IMAGE_MAX_DIMENSION: z.coerce
@@ -662,6 +662,16 @@ export const pgModerationActionsTable = pgTable(
    error: pgText("error"),
    created_at: pgBigint("created_at", { mode: "number" }).notNull(),
    executed_at: pgBigint("executed_at", { mode: "number" }),
+    // ── Explainability (structured verdict; surfaced read-only to public web) ──
+    flags: pgText("flags"), // JSON array of string flags, e.g. ["sara_agama","vulgar"]
+    categories: pgText("categories"), // JSON array of category strings
+    severity: pgText("severity", {
+      enum: ["none", "low", "medium", "high", "critical"],
+    }),
+    confidence: pgReal("confidence"), // 0..1
+    score: pgReal("score"), // 0..1 raw model score
+    evidence: pgText("evidence"), // JSON array of short quoted snippets
+    policy_version: pgText("policy_version"), // rules.ts policy version string
  },
  (table) => ({
    messageIdIdx: pgIndex("idx_moderation_actions_message_id").on(
@@ -2,6 +2,7 @@ import {
  bigint as pgBigint,
  boolean as pgBoolean,
  index as pgIndex,
+  real as pgReal,
  pgTable,
  text as pgText,
  uuid as pgUuid,
@@ -48,6 +49,16 @@ export const pgModerationActionsTable = pgTable(
    error: pgText("error"),
    created_at: pgBigint("created_at", { mode: "number" }).notNull(),
    executed_at: pgBigint("executed_at", { mode: "number" }),
+    // ── Explainability (structured verdict; surfaced read-only to public web) ──
+    flags: pgText("flags"), // JSON array of string flags, e.g. ["sara_agama","vulgar"]
+    categories: pgText("categories"), // JSON array of category strings
+    severity: pgText("severity", {
+      enum: ["none", "low", "medium", "high", "critical"],
+    }),
+    confidence: pgReal("confidence"), // 0..1
+    score: pgReal("score"), // 0..1 raw model score
+    evidence: pgText("evidence"), // JSON array of short quoted snippets
+    policy_version: pgText("policy_version"), // rules.ts policy version string
  },
  (table) => ({
    messageIdIdx: pgIndex("idx_moderation_actions_message_id").on(
@@ -34,6 +34,7 @@ import {
  useMessagesHasMore,
  useMessagesStream,
  useMessagesWsSync,
+  useSemanticSearch,
 } from "@/hooks";
 import { aiTone } from "@/lib/ai-status";
 import {
@@ -67,6 +68,9 @@ export function MessagesView({
  const [channelId, setChannelId] = useState<string | null>(null);
  const [selected, setSelected] = useState<string | null>(null);
  const [query, setQuery] = useState("");
+  // Search mode: "exact" (substring match over captured messages) or
+  // "semantic" (vector similarity over the persistent Qdrant archive).
+  const [semanticMode, setSemanticMode] = useState(false);
  // Guard against loading the entire history on a long scroll: cap how many
  // older pages we append. Each page is 50 messages (backend limit default).
  const MAX_OLDER_PAGES = 10;
@@ -94,7 +98,14 @@ export function MessagesView({
  const hasMore = pageInfo?.hasMore ?? false;
  const loadMore = useLoadMore();
  useMessagesWsSync(ws, guildId ?? "");
-  const search = useMessageSearch(query, query.trim().length >= 2);
+  const search = useMessageSearch(
+    query,
+    query.trim().length >= 2 && !semanticMode,
+  );
+  const semantic = useSemanticSearch(
+    query,
+    query.trim().length >= 2 && semanticMode,
+  );
  const detail = useMessageDetail(selected);
  const ambient = useAmbient();

@@ -122,7 +133,8 @@ export function MessagesView({
    ambient.set(query ? "amber" : "signal", 0.3, query ? "search" : "messages");
  }, [query, ambient]);

-  const searching = query.trim().length >= 2;
+  const searching = query.trim().length >= 2 && !semanticMode;
+  const semanticSearching = query.trim().length >= 2 && semanticMode;
  const list = searching ? (search.data ?? []) : (messages ?? []);
  // Discord-style order: oldest at the top, newest at the bottom. The backend
  // returns DESC (newest first); reverse so the feed reads top→bottom like DC.
@@ -184,9 +196,68 @@ export function MessagesView({
            onChange={(e) => setQuery(e.target.value)}
          />
        </div>
+        <button
+          type="button"
+          onClick={() => setSemanticMode((v) => !v)}
+          className={`rounded-full border px-3 py-1.5 text-xs transition-colors ${
+            semanticMode
+              ? "border-signal/40 bg-signal/10 text-signal"
+              : "border-hairline bg-white/[0.03] text-ink-soft hover:bg-white/[0.06]"
+          }`}
+          title="Toggle semantic (vector) search over the message archive"
+        >
+          {semanticMode ? "Semantic" : "Exact"}
+        </button>
      </GlassPanel>

      <div className="grid gap-4 lg:grid-cols-5">
+        {semanticSearching && (
+          <GlassPanel className="lg:col-span-5">
+            <SectionHeader
+              eyebrow="semantic"
+              title={`“${query}”`}
+              action={
+                <span className="mono text-xs text-ink-faint">
+                  {semantic.data?.length ?? 0} matches
+                </span>
+              }
+            />
+            {semantic.isLoading ? (
+              <SkeletonRows rows={4} />
+            ) : semantic.data && semantic.data.length > 0 ? (
+              <div className="max-h-[60vh] space-y-1.5 overflow-y-auto pr-1">
+                {semantic.data.map((r, i) => (
+                  <div
+                    key={r.message_id ?? i}
+                    className="animate-stagger flex items-start gap-3 rounded-[10px] border border-hairline bg-white/[0.03] p-3"
+                    style={staggerDelay(i)}
+                  >
+                    <div className="min-w-0 flex-1">
+                      <div className="flex items-center gap-2">
+                        <span className="mono text-[0.6rem] text-signal">
+                          {(r.score * 100).toFixed(0)}%
+                        </span>
+                        <span className="mono ml-auto text-[0.6rem] text-ink-faint">
+                          {formatRelativeTime(r.created_at)}
+                        </span>
+                      </div>
+                      <div className="mt-0.5 line-clamp-3 text-sm text-ink-soft">
+                        {r.content}
+                      </div>
+                    </div>
+                  </div>
+                ))}
+              </div>
+            ) : (
+              <EmptyState
+                icon={<Search className="size-7" />}
+                title="No semantic matches"
+                description="Try different wording — semantic search finds meaning, not exact text."
+              />
+            )}
+          </GlassPanel>
+        )}
+
        <GlassPanel className="lg:col-span-3">
          <SectionHeader
            eyebrow={searching ? "results" : "live feed"}
@@ -31,6 +31,7 @@ import {
  SkeletonRows,
 } from "@/components/shared";
 import { useModerationActions, useModerationStats } from "@/hooks";
+import { aiTone } from "@/lib/ai-status";
 import { formatNumber, formatRelativeTime } from "@/lib/format";
 import type {
  ModerationAction,
@@ -243,6 +244,18 @@ function ActionRow({ a, index = 0 }: { a: ModerationAction; index?: number }) {
  const icon = ACTION_ICON[a.action_type] ?? (
    <AlertTriangle className="size-3.5" />
  );
+  // Map moderation severity → design-system tone (reuse aiTone with a
+  // severity→status projection so "none" reads as clean/signal).
+  const severityTone =
+    a.severity == null
+      ? null
+      : aiTone(
+          a.severity === "none"
+            ? "clean"
+            : a.severity === "low" || a.severity === "medium"
+              ? "warn"
+              : "flagged",
+        );
  return (
    <div
      className="animate-stagger flex items-start gap-3 rounded-[10px] border border-hairline bg-white/[0.03] p-3"
@@ -266,6 +279,30 @@ function ActionRow({ a, index = 0 }: { a: ModerationAction; index?: number }) {
        {a.reason && (
          <div className="mt-0.5 text-xs text-ink-soft">“{a.reason}”</div>
        )}
+        {severityTone && a.severity && (
+          <div className="mt-1 flex flex-wrap items-center gap-1">
+            <Badge tone={severityTone}>{a.severity}</Badge>
+            {a.confidence != null && (
+              <span className="mono text-[0.6rem] text-ink-faint">
+                conf {(a.confidence * 100).toFixed(0)}%
+              </span>
+            )}
+          </div>
+        )}
+        {a.flags?.length ? (
+          <div className="mt-1 flex flex-wrap gap-1">
+            {a.flags.slice(0, 6).map((f) => (
+              <Badge key={f} tone="amber">
+                {f}
+              </Badge>
+            ))}
+          </div>
+        ) : null}
+        {a.evidence?.length ? (
+          <div className="mt-1 border-l-2 border-hairline pl-2 text-xs text-ink-faint">
+            &ldquo;{a.evidence[0]}&rdquo;
+          </div>
+        ) : null}
        {a.executed_by && (
          <div className="mono mt-0.5 text-[0.6rem] text-ink-faint">
            by {a.executed_by}
@@ -28,6 +28,7 @@ export {
  useMessagesStream,
  useMessagesWsSync,
  useReview,
+  useSemanticSearch,
  useTextChannels,
 } from "./use-messages";
 export {
@@ -2,7 +2,12 @@ import { useEffect, useState } from "react";
 import useSWR, { useSWRConfig } from "swr";
 import { useAction } from "@/hooks/use-action";
 import { messagesApi, voiceApi } from "@/lib/api";
-import type { AttachmentRecord, Channel, MessageRecord } from "@/lib/types";
+import type {
+  AttachmentRecord,
+  Channel,
+  MessageRecord,
+  SemanticSearchResult,
+} from "@/lib/types";
 import type { WsHook } from "@/lib/ws-hook";

 // ── Query keys factory ───────────────────────────
@@ -177,6 +182,21 @@ export function useMessageSearch(query: string, enabled: boolean) {
  );
 }

+// ── Semantic Search (public archive, Qdrant) ──────
+
+export function useSemanticSearch(query: string, enabled: boolean) {
+  return useSWR<SemanticSearchResult[]>(
+    enabled && query.trim().length >= 2
+      ? ["semantic-search", query.trim()]
+      : null,
+    async () => {
+      const res = await messagesApi.semanticSearch(query.trim(), 10);
+      return res.results;
+    },
+    { keepPreviousData: true },
+  );
+}
+
 // ── WS sync helpers ──────────────────────────────

 export function useMessagesWsSync(ws: WsHook, guildId: string) {
@@ -1,5 +1,9 @@
 import { orpc } from "@/lib/orpc/client";
-import type { AttachmentRecord, MessageRecord } from "@/lib/types";
+import type {
+  AttachmentRecord,
+  MessageRecord,
+  SemanticSearchResult,
+} from "@/lib/types";

 export const messagesApi = {
  list: (
@@ -62,4 +66,11 @@ export const messagesApi = {
    orpc.analysis.search({ q, limit }) as unknown as Promise<{
      results: MessageRecord[];
    }>,
+
+  // Public semantic search over the persistent message archive (Qdrant).
+  semanticSearch: (query: string, limit?: number) =>
+    orpc.messages.semanticSearch({ query, limit }) as unknown as Promise<{
+      results: SemanticSearchResult[];
+      nextCursor: null;
+    }>,
 };
@@ -163,3 +163,17 @@ export interface AttachmentRecord {
  created_at: number;
  uploaded_at?: number | null;
 }
+
+// ── Semantic Search (read-only public archive search) ──────────
+
+export interface SemanticSearchResult {
+  message_id: string | null;
+  content: string;
+  score: number;
+  created_at: number;
+}
+
+export interface SemanticSearchResponse {
+  results: SemanticSearchResult[];
+  nextCursor: null;
+}
@@ -21,6 +21,14 @@ export interface ModerationAction {
  executed_at: number | null;
  username: string | null;
  content: string | null;
+  // ── Explainability (structured verdict, surfaced read-only to public web) ──
+  flags: string[] | null;
+  categories: string[] | null;
+  severity: "none" | "low" | "medium" | "high" | "critical" | null;
+  confidence: number | null;
+  score: number | null;
+  evidence: string[] | null;
+  policy_version: string | null;
 }

 export interface ModerationStats {