Files
GMW/services/discord-gateway/src/modules/ai-moderation/moderationBuilders.ts
T
asepharyana 65c9c2cd9e feat(ai-moderation): enrich analysis context with recency, repetition, user history and channel topic
- <message> targets now carry time (ISO), repetitions (N identical short texts = spam signal), bot and edited flags; escape id/user XML
- rich <user_reputation>: total_infractions, clean_streak, last_offense_days_ago, repeat_offender (7-day window)
- <user_history> with last flagged messages for repeat offenders (wires dead getUserRecentInfractions)
- <user_profile as_of> staleness signal; <location_context topic> from captured channel topic
- prompt framing + output instructions teach the LLM to use the new signals without treating history as proof
- tests: contextEnrichment.test.ts (13) + topic cases in conversationContext.test.ts
2026-08-10 17:15:33 +07:00

323 lines
12 KiB
TypeScript

/**
* moderationBuilders.ts
*
* Shared builder utilities extracted from llmModerationClient.ts.
* Used by both mediaAnalysisClient.ts and moderationOrchestrator.ts.
*/
import { renderDiscordMentions } from "../message-capture/messageMetadata.js";
import { messageStore } from "../message-capture/messageStore.js";
import type { MessageRecord } from "../message-capture/types.js";
import { sanitizeDiscordTokens } from "./discordTokens.js";
import { sanitizeAiContent } from "./prompts/output.js";
/** Simple XML-escaping for content text. */
export function escapeXml(s: string): string {
return s
.replace(/&/g, "&amp;")
.replace(/</g, "&lt;")
.replace(/>/g, "&gt;")
.replace(/"/g, "&quot;");
}
// ---------------------------------------------------------------------------
// Conversation context block — structured data for the USER message.
//
// All per-batch context lives in the USER message (not the SYSTEM prompt) so
// the system prompt is stable per mode (cacheable on routers/providers) and
// the role boundary is clean: instructions in SYSTEM, data in USER.
// ---------------------------------------------------------------------------
/** Outer char cap for the assembled `<conversation_context>` inner text. */
export const CONVERSATION_CONTEXT_MAX_CHARS = 40_000;
/**
* Wraps per-batch context data into structured XML blocks for the USER
* message:
*
* <location_context channel_id="..." channel_name="..." nsfw="..."/>
* <conversation_context>
* [conversation_flow] status=ongoing context_msgs=12 dropped=0
* [context] id=... time=... user=...: isi pesan
* ...
* </conversation_context>
*
* Empty blocks are omitted entirely (never emit a hollow `<conversation_context>`
* with no content). The inner text is AI/user-derived and passed through
* `sanitizeAiContent` (CDATA + XML-escape) to block prompt injection.
*/
export function buildConversationContextBlock(input: {
/** Pre-built `<location_context .../>` string (or ""). */
location?: string;
/** `[conversation_flow]` descriptor line from buildConversationContext. */
descriptor?: string;
/** `[context]` lines, oldest → newest. */
lines: string[];
}): string {
const blocks: string[] = [];
const location = input.location?.trim();
if (location) blocks.push(location);
const inner = [input.descriptor ?? "", ...input.lines]
.map((line) => line.trim())
.filter((line) => line.length > 0)
.join("\n");
if (inner) {
blocks.push(
`<conversation_context>\n${sanitizeAiContent(inner, CONVERSATION_CONTEXT_MAX_CHARS)}\n</conversation_context>`,
);
}
return blocks.join("\n");
}
// ---------------------------------------------------------------------------
// Per-message content bounds — protects the LLM token budget from a single
// huge paste (stack traces, log dumps, copypasta). Truncation is explicit so
// the model never mistakes the cut for a real message boundary.
// ---------------------------------------------------------------------------
/** Max characters of a message's content sent to the LLM `<content>` payload. */
export const AI_CONTENT_MAX_CHARS = 4000;
/** Marker appended when a message is longer than AI_CONTENT_MAX_CHARS. */
export const AI_CONTENT_TRUNC_MARKER = "\n…[pesan dipotong: terlalu panjang]";
/** Truncate a message's content for the LLM `<content>` payload. */
export function truncateForAi(content: string): string {
if (content.length <= AI_CONTENT_MAX_CHARS) return content;
return `${content.slice(0, AI_CONTENT_MAX_CHARS)}${AI_CONTENT_TRUNC_MARKER}`;
}
// ---------------------------------------------------------------------------
// User profile deduplication — a batch can contain many messages from the
// same user. Instead of repeating the (up to 3000-char) profile summary on
// every message, emit a single <user_profiles> map per batch and reference
// entries per message with <user_profile_ref user_id="..."/>.
// ---------------------------------------------------------------------------
export interface UserProfileEntry {
/** Profile summary text (from user_profiles.profile_summary). */
text: string;
/** Epoch ms when the profile was last generated — staleness signal for
* the LLM (a profile from months ago may not reflect current behavior). */
asOf?: number | null;
}
/** Build a deduplicated `<user_profiles>` map block, keyed by Discord user id. */
export function buildUserProfilesBlock(
profiles: ReadonlyMap<string, UserProfileEntry>,
): string {
const entries = Array.from(profiles.entries()).filter(
([, entry]) => entry.text.trim().length > 0,
);
if (entries.length === 0) return "";
const lines = entries.map(([userId, entry]) => {
const asOfAttr =
typeof entry.asOf === "number" && entry.asOf > 0
? ` as_of="${new Date(entry.asOf).toISOString()}"`
: "";
return ` <user_profile user_id="${escapeXml(userId)}"${asOfAttr}>${sanitizeAiContent(entry.text)}</user_profile>`;
});
return `<user_profiles>\n${lines.join("\n")}\n</user_profiles>`;
}
/** Per-message reference tag pointing at an entry in the `<user_profiles>` map. */
export function buildUserProfileRef(userId: string): string {
return `<user_profile_ref user_id="${escapeXml(userId)}"/>`;
}
// ---------------------------------------------------------------------------
// User reputation — richer than a bare trust score.
//
// The trust model tracks total_infractions, a clean-message streak and the
// last infraction timestamp. Feeding all of it to the LLM lets it tell a
// first-timer (same score, 1 infraction) from a repeat offender (score 50,
// 3 infractions, last one yesterday) — the same score means very different
// things in those two contexts.
// ---------------------------------------------------------------------------
export interface ReputationAttrsSource {
trust_score: number;
total_infractions: number;
clean_message_streak: number;
last_infraction_at: number | null;
}
const DAY_MS = 24 * 60 * 60 * 1000;
const REPEAT_OFFENSE_WINDOW_MS = 7 * DAY_MS;
/**
* Formats reputation fields into XML attributes for `<user_reputation .../>`.
* Derived signals: last_offense_days_ago (0 = today) and repeat_offender
* (infraction within the last 7 days) are computed here so both the text and
* media paths emit the exact same shape.
*/
export function formatReputationAttrs(
rep: ReputationAttrsSource,
now: number = Date.now(),
): string {
const attrs = [
`trust_score="${rep.trust_score}"`,
`total_infractions="${rep.total_infractions}"`,
`clean_streak="${rep.clean_message_streak}"`,
];
if (
typeof rep.last_infraction_at === "number" &&
rep.last_infraction_at > 0
) {
const daysAgo = Math.max(
0,
Math.floor((now - rep.last_infraction_at) / DAY_MS),
);
attrs.push(`last_offense_days_ago="${daysAgo}"`);
const isRepeat =
rep.total_infractions > 0 &&
now - rep.last_infraction_at <= REPEAT_OFFENSE_WINDOW_MS;
if (isRepeat) attrs.push(`repeat_offender="true"`);
}
return attrs.join(" ");
}
/**
* Builds an optional `<user_history>` block (last flagged messages) from
* getUserRecentInfractions rows. Only emitted when there is real history —
* lets the LLM see the PATTERN (e.g. the same scam link posted repeatedly)
* without treating old flags as proof for the current message.
*/
export function buildUserHistoryXml(
history: Array<{
content: string;
severity: string | null;
created_at: number;
}>,
now: number = Date.now(),
): string {
const filtered = history.filter((h) => h.content?.trim());
if (filtered.length === 0) return "";
const lines = filtered.map((h) => {
const daysAgo = Math.max(0, Math.floor((now - h.created_at) / DAY_MS));
const severityAttr = h.severity
? ` severity="${escapeXml(h.severity)}"`
: "";
const snippet =
h.content.length > 100
? `${h.content.slice(0, 100).trimEnd()}…`
: h.content;
return ` <infraction${severityAttr} time_ago_days="${daysAgo}">${escapeXml(snippet)}</infraction>`;
});
return `<user_history>\n${lines.join("\n")}\n</user_history>`;
}
/**
* Whether the message author was a bot (captured in metadata.author.bot).
* Bot posts (logging bots, webhook-style automation) deserve different
* scrutiny than user posts — expose the flag instead of hiding it.
*/
export function resolveIsBot(msg: MessageRecord): boolean {
if (!msg.metadata) return false;
try {
const meta = JSON.parse(msg.metadata) as {
author?: { bot?: boolean } | null;
};
return Boolean(meta?.author?.bot);
} catch {
return false;
}
}
/** Whether the shown content is an EDIT of the original post (evasion signal). */
export function resolveIsEdited(msg: MessageRecord): boolean {
return Boolean(msg.edited_content);
}
/**
* Returns the real text content for AI analysis, stripping fallback text
* that getDisplayContent() synthesized ("[Attachment: ...]", "[Sticker: ...]",
* "[Embed]"). These filenames alone are meaningless to the LLM and can
* falsely inflate a "clean" verdict when the actual image failed to download.
*/
export function getAnalysisContent(message: MessageRecord): string {
const raw = message.edited_content ?? message.content;
const stripped = raw.replace(
/\[(?:Attachment|Sticker):[^\]]*\]|\[Embed\]/g,
"",
);
return sanitizeDiscordTokens(
renderDiscordMentions(stripped, message.metadata),
).trim();
}
/**
* Server nickname (member.displayName) when captured, else the author
* username. Discord shows the server nickname to other members, so the LLM
* should see the same name the channel sees — and a nickname can carry
* moderation signal itself (offensive nick + clean message → low warn).
*/
export function resolveDisplayName(msg: MessageRecord): string {
if (msg.metadata) {
try {
const meta = JSON.parse(msg.metadata) as {
member?: { displayName?: string | null } | null;
};
const dn = meta?.member?.displayName;
if (dn && dn.trim().length > 0) return dn;
} catch {
// malformed metadata — fall back to username
}
}
return msg.username;
}
/**
* Builds a <reference> XML element for reply/forward/crosspost context.
*/
export async function buildReferenceXml(msg: MessageRecord): Promise<string> {
const parts: string[] = [];
if (msg.is_reply && msg.reference_message_id) {
parts.push(`type="reply"`);
} else if (msg.is_forward && msg.reference_message_id) {
parts.push(`type="forward"`);
}
if (msg.is_crosspost) {
parts.push(`type="crosspost"`);
}
if (!msg.reference_message_id) return "";
let parentContent = "";
if (msg.reference_message_id) {
// 1. Try DB first — works for messages captured in the same server
try {
const parent = await messageStore.getMessageById(
msg.reference_message_id,
);
if (parent) {
const parentText = parent.edited_content ?? parent.content;
parentContent = parentText.slice(0, 500);
}
} catch {
// Parent fetch failed — fall through to metadata
}
// 2. Fall back to metadata — works for forwards from other servers/channels
// where the original message was never captured in this DB.
// The capture phase stores the snapshot content in metadata.reference.content.
if (!parentContent && msg.metadata) {
try {
const meta = JSON.parse(msg.metadata);
const refContent = meta?.reference?.content;
if (refContent && typeof refContent === "string") {
parentContent = refContent.slice(0, 500);
}
} catch {
// Metadata parse failed — no fallback available
}
}
}
const attr = parts.join(" ");
const parentXml = parentContent
? `<parent_content>${escapeXml(parentContent)}</parent_content>`
: "";
return `<reference ${attr} message_id="${msg.reference_message_id}" channel_id="${msg.reference_channel_id ?? ""}" guild_id="${msg.reference_guild_id ?? ""}">${parentXml}</reference>`;
}