feat: add AI analysis integration with moderation and LLM processing
This commit is contained in:
MythEclipse
@@ -34,6 +34,34 @@ const configSchema = z.object({
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ATTACHMENT_RETRY_ATTEMPTS: z.coerce.number().positive().default(3),
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BACKLOG_SYNC_HOURS: z.coerce.number().positive().default(24),
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BACKLOG_SYNC_BATCH_SIZE: z.coerce.number().int().positive().max(100).default(100),
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AI_ANALYSIS_ENABLED: z
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.string()
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.optional()
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.transform((v) => v === "true")
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.default(false),
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OPENAI_MODERATION_API_KEY: z.string().optional(),
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OPENAI_MODERATION_BASE_URL: z.string().url().default("https://api.openai.com/v1"),
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OPENAI_MODERATION_MODEL: z.string().default("omni-moderation-latest"),
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AI_LLM_API_KEY: z.string().optional(),
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AI_LLM_BASE_URL: z.string().url().default("https://9router.asepharyana.tech/v1"),
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AI_LLM_MODEL: z.string().default("free"),
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AI_ANALYSIS_TIMEOUT_MS: z.coerce.number().positive().default(30000),
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}).superRefine((value, ctx) => {
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if (!value.AI_ANALYSIS_ENABLED) return;
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if (!value.OPENAI_MODERATION_API_KEY) {
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ctx.addIssue({
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code: z.ZodIssueCode.custom,
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path: ["OPENAI_MODERATION_API_KEY"],
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message: "OPENAI_MODERATION_API_KEY is required when AI_ANALYSIS_ENABLED=true",
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});
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}
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if (!value.AI_LLM_API_KEY) {
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ctx.addIssue({
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code: z.ZodIssueCode.custom,
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path: ["AI_LLM_API_KEY"],
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message: "AI_LLM_API_KEY is required when AI_ANALYSIS_ENABLED=true",
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});
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}
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});
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export type AppConfig = z.infer<typeof configSchema>;
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@@ -0,0 +1,169 @@
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import { config } from "../config";
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import { createChildLogger } from "../logger";
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import type { SqliteDatabase } from "../muxer-queue";
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import { retryWithBackoff } from "../retry";
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import { getMessageById, updateMessageAIAnalysis } from "./messageStore";
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import type { MessageRecord } from "./types";
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const logger = createChildLogger("ai-analyzer");
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const queuedMessageIds = new Set<string>();
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let isProcessing = false;
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interface ModerationResult {
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flagged: boolean;
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flags: string[];
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score: number;
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raw: unknown;
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}
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interface ChatCompletionResponse {
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choices?: Array<{
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message?: {
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content?: string;
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};
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}>;
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}
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function getAnalysisText(message: MessageRecord): string {
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return (message.edited_content || message.content || "").trim();
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}
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async function fetchJson(url: string, init: RequestInit): Promise<unknown> {
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const controller = new AbortController();
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const timeout = setTimeout(() => controller.abort(), config.AI_ANALYSIS_TIMEOUT_MS);
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try {
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const response = await fetch(url, { ...init, signal: controller.signal });
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const body = await response.json().catch(() => ({}));
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if (!response.ok) {
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const message = typeof body === "object" && body && "error" in body
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? JSON.stringify(body)
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: response.statusText;
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throw new Error(`AI request failed (${response.status}): ${message}`);
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}
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return body;
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} finally {
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clearTimeout(timeout);
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}
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}
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async function runModeration(text: string): Promise<ModerationResult> {
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const response = await retryWithBackoff(
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() => fetchJson(`${config.OPENAI_MODERATION_BASE_URL}/moderations`, {
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method: "POST",
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headers: {
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"Authorization": `Bearer ${config.OPENAI_MODERATION_API_KEY}`,
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"Content-Type": "application/json",
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},
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body: JSON.stringify({
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model: config.OPENAI_MODERATION_MODEL,
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input: text,
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}),
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}),
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{ retries: 2, logger },
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) as any;
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const result = response.results?.[0] || {};
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const categories = result.categories || {};
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const categoryScores = result.category_scores || {};
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const flags = Object.entries(categories)
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.filter(([, flagged]) => Boolean(flagged))
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.map(([name]) => name);
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const score = Math.max(0, ...Object.values(categoryScores).map((value) => Number(value) || 0));
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return {
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flagged: Boolean(result.flagged) || flags.length > 0,
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flags,
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score,
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raw: response,
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};
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}
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async function runLLMAnalysis(text: string, moderation: ModerationResult): Promise<string> {
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const response = await retryWithBackoff(
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() => fetchJson(`${config.AI_LLM_BASE_URL}/chat/completions`, {
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method: "POST",
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headers: {
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"Authorization": `Bearer ${config.AI_LLM_API_KEY}`,
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"Content-Type": "application/json",
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},
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body: JSON.stringify({
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model: config.AI_LLM_MODEL,
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messages: [
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{
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role: "system",
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content: "Kamu analis moderation Discord. Jawab singkat dalam Bahasa Indonesia: ringkasan risiko, alasan, dan aksi yang disarankan. Jangan mengulang pesan mentah secara panjang.",
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},
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{
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role: "user",
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content: JSON.stringify({
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message: text,
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moderationFlagged: moderation.flagged,
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moderationFlags: moderation.flags,
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moderationScore: moderation.score,
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}),
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},
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],
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temperature: 0.2,
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}),
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}),
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{ retries: 2, logger },
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) as ChatCompletionResponse;
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return response.choices?.[0]?.message?.content?.trim() || "Tidak ada analisis dari LLM.";
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}
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async function analyzeAndStore(db: SqliteDatabase, message: MessageRecord): Promise<void> {
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const text = getAnalysisText(message);
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if (!config.AI_ANALYSIS_ENABLED || text.length === 0) return;
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try {
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const moderation = await runModeration(text);
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const analysis = await runLLMAnalysis(text, moderation);
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const row = updateMessageAIAnalysis(db, message.id, {
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status: moderation.flagged ? "flagged" : "clean",
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flags: JSON.stringify(moderation.flags),
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score: moderation.score,
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raw: JSON.stringify(moderation.raw),
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analysis,
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analyzedAt: Date.now(),
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error: null,
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});
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if (row) (globalThis as any).broadcastMessageAnalyzed?.(row);
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} catch (error) {
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const row = updateMessageAIAnalysis(db, message.id, {
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status: "error",
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flags: null,
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score: null,
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raw: null,
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analysis: null,
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analyzedAt: Date.now(),
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error: error instanceof Error ? error.message : String(error),
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});
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if (row) (globalThis as any).broadcastMessageAnalyzed?.(row);
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logger.warn({ messageId: message.id, error }, "AI analysis failed");
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}
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}
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async function drainQueue(db: SqliteDatabase): Promise<void> {
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if (isProcessing) return;
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isProcessing = true;
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try {
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while (queuedMessageIds.size > 0) {
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const [messageId] = queuedMessageIds;
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queuedMessageIds.delete(messageId);
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const message = getMessageById(db, messageId);
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if (message) await analyzeAndStore(db, message);
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}
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} finally {
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isProcessing = false;
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}
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}
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export function queueMessageAnalysis(db: SqliteDatabase, messageId: string): void {
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if (!config.AI_ANALYSIS_ENABLED) return;
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queuedMessageIds.add(messageId);
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setImmediate(() => {
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drainQueue(db).catch((error) => logger.error({ error }, "AI analysis queue failed"));
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});
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}
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@@ -5,6 +5,7 @@ import { config } from "../config";
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import { insertMessage, insertAttachment } from "./messageStore";
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import { processAttachmentUpload } from "./attachmentUploader";
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import { getDisplayContent, getMessageLocation, getMessageMetadata } from "./messageMetadata";
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import { queueMessageAnalysis } from "./aiAnalyzer";
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import type { MessageRecord, AttachmentRecord } from "./types";
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const logger = createChildLogger("message-capture");
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@@ -35,6 +36,7 @@ export async function captureMessage(
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};
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insertMessage(db, messageRecord);
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queueMessageAnalysis(db, message.id);
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const broadcaster = globalThis as any;
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if (broadcaster.broadcastMessageCreated) {
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@@ -126,6 +128,7 @@ export function registerMessageCapture(client: Client, db: SqliteDatabase): void
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if (existing) {
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const editedAt = Date.now();
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updateMessageAsEdited(db, newMessage.id, getDisplayContent(newMessage as Message), editedAt);
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queueMessageAnalysis(db, newMessage.id);
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const broadcaster = globalThis as any;
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if (broadcaster.broadcastMessageUpdated) {
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@@ -220,3 +220,76 @@ export function updateAttachmentAsFailedUpload(
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throw error;
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}
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}
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interface AIAnalysisUpdate {
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status: "pending" | "clean" | "flagged" | "error";
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flags?: string | null;
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score?: number | null;
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raw?: string | null;
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analysis?: string | null;
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analyzedAt?: number | null;
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error?: string | null;
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}
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export function updateMessageAIAnalysis(
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db: SqliteDatabase,
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messageId: string,
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result: AIAnalysisUpdate,
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): MessageRecord | null {
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try {
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const stmt = db.prepare(`
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UPDATE messages
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SET ai_status = ?, ai_moderation_flags = ?, ai_moderation_score = ?,
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ai_moderation_raw = ?, ai_analysis = ?, ai_analyzed_at = ?, ai_error = ?
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WHERE id = ?
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`);
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stmt.run(
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result.status,
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result.flags ?? null,
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result.score ?? null,
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result.raw ?? null,
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result.analysis ?? null,
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result.analyzedAt ?? Date.now(),
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result.error ?? null,
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messageId,
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);
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const row = db.prepare("SELECT * FROM messages WHERE id = ?").get(messageId) as MessageRecord | undefined;
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return row ?? null;
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} catch (error) {
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logger.error(
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{ messageId, error: error instanceof Error ? error.message : String(error) },
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"Failed to update message AI analysis",
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);
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throw error;
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}
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}
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export function getPendingAIAnalysisMessages(
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db: SqliteDatabase,
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limit: number = 25,
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): MessageRecord[] {
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try {
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const stmt = db.prepare(`
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SELECT * FROM messages
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WHERE ai_status = 'pending'
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AND deleted_at IS NULL
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AND COALESCE(edited_content, content) != ''
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ORDER BY created_at ASC
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LIMIT ?
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`);
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return stmt.all(limit) as MessageRecord[];
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} catch (error) {
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logger.error(
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{ error: error instanceof Error ? error.message : String(error) },
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"Failed to get pending AI analysis messages",
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);
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throw error;
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}
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}
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export function getMessageById(db: SqliteDatabase, messageId: string): MessageRecord | null {
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const row = db.prepare("SELECT * FROM messages WHERE id = ?").get(messageId) as MessageRecord | undefined;
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return row ?? null;
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}
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@@ -13,6 +13,13 @@ export interface MessageRecord {
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deleted_at: number | null;
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type: "text" | "edited" | "deleted";
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metadata: string | null;
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ai_status?: "pending" | "clean" | "flagged" | "error" | null;
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ai_moderation_flags?: string | null;
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ai_moderation_score?: number | null;
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ai_moderation_raw?: string | null;
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ai_analysis?: string | null;
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ai_analyzed_at?: number | null;
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ai_error?: string | null;
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}
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export interface AttachmentRecord {
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+25
-5
@@ -71,7 +71,14 @@ function initializeDatabase(): SqliteDatabase {
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edited_at INTEGER,
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deleted_at INTEGER,
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type TEXT NOT NULL DEFAULT 'text',
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metadata TEXT
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metadata TEXT,
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ai_status TEXT NOT NULL DEFAULT 'pending',
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ai_moderation_flags TEXT,
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ai_moderation_score REAL,
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ai_moderation_raw TEXT,
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ai_analysis TEXT,
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ai_analyzed_at INTEGER,
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ai_error TEXT
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);
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CREATE INDEX IF NOT EXISTS idx_messages_channel ON messages(channel_id);
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@@ -103,10 +110,23 @@ function initializeDatabase(): SqliteDatabase {
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CREATE INDEX IF NOT EXISTS idx_attachments_status ON attachments(upload_status);
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`);
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try {
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database.exec("ALTER TABLE attachments ADD COLUMN thread_id TEXT");
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} catch {
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// Column already exists on databases initialized after the moderation schema was added.
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const migrations = [
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"ALTER TABLE attachments ADD COLUMN thread_id TEXT",
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"ALTER TABLE messages ADD COLUMN ai_status TEXT NOT NULL DEFAULT 'pending'",
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"ALTER TABLE messages ADD COLUMN ai_moderation_flags TEXT",
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"ALTER TABLE messages ADD COLUMN ai_moderation_score REAL",
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"ALTER TABLE messages ADD COLUMN ai_moderation_raw TEXT",
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"ALTER TABLE messages ADD COLUMN ai_analysis TEXT",
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"ALTER TABLE messages ADD COLUMN ai_analyzed_at INTEGER",
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"ALTER TABLE messages ADD COLUMN ai_error TEXT",
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];
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for (const migration of migrations) {
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try {
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database.exec(migration);
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} catch {
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// Column already exists on databases initialized after schema updates.
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}
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}
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return database;
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@@ -324,6 +324,10 @@ export function startWebserver(
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broadcastMessageEvent("attachment_uploaded", data);
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};
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(global as any).broadcastMessageAnalyzed = (data: any) => {
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broadcastMessageEvent("message_analyzed", data);
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};
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// --- Outbound: browser PCM (24kHz mono) → Opus → Discord ---
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const RATE = 48000;
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const CHANNELS = 2;
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