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GMW/src/moderation/aiAnalyzer.ts
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import { existsSync } from "node:fs";
import { fileURLToPath } from "node:url";
import type { Client } from "discord.js-selfbot-v13";
import { AbortError } from "p-retry";
import { Piscina } from "piscina";
import { config } from "../config.js";
import { createChildLogger } from "../logger.js";
import { retryWithBackoff } from "../retry.js";
import { attemptAutoDeleteFlaggedMessage } from "./autoDeleteManager.js";
import {
buildConversationContext,
estimateTokens,
formatMessageForPrompt,
} from "./conversationContext.js";
import { runModerationAnalysis } from "./llmModerationClient.js";
import {
getAttachmentsForMessages,
getConversationContextBefore,
getConversationKeysWithIncompleteAnalysis,
getIncompleteMessagesByConversation,
getMessageById,
getPendingConversationKeys,
getPendingMessagesByConversation,
updateMessagesAIAnalysisBulk,
} from "./messageStore.js";
import type {
AnalysisQueueStatus,
MessageRecord,
ModerationBroadcaster,
} from "./types.js";
const logger = createChildLogger("ai-analyzer");
type ModerationGlobal = typeof globalThis & {
moderationBroadcaster?: ModerationBroadcaster;
};
function getModerationBroadcaster(): ModerationBroadcaster | undefined {
return (globalThis as ModerationGlobal).moderationBroadcaster;
}
function scheduleAutoDelete(row: MessageRecord): void {
if (row.ai_status !== "flagged" && row.ai_status !== "warn") return;
const run = () => {
attemptAutoDeleteFlaggedMessage(moderationClient, row).catch((error) => {
logger.error(
{
messageId: row.id,
error: error instanceof Error ? error.message : String(error),
},
"Unexpected auto-delete error",
);
});
};
if (config.AUTO_DELETE_FLAGGED_DELAY_MS > 0) {
setTimeout(run, config.AUTO_DELETE_FLAGGED_DELAY_MS);
return;
}
setImmediate(run);
}
// ---------------------------------------------------------------------------
// Batch pipeline state
// ---------------------------------------------------------------------------
/** Debounce timer handle per conversation key. */
const conversationDebounceTimers = new Map<string, NodeJS.Timeout>();
/** Timestamp of when processing started per conversation key. */
const conversationProcessing = new Map<string, number>();
/** Cooldown expiry timestamp per conversation key after an error. */
const conversationErrorCooldown = new Map<string, number>();
let activeRequests = 0;
let lastError: string | null = null;
let moderationClient: Client | undefined;
// Batch circuit breaker
let consecutiveErrors = 0;
const MAX_CONSECUTIVE_ERRORS = 5;
let globalCooldownUntil = 0;
// ---------------------------------------------------------------------------
// Individual fallback queue — runs PARALLEL to the batch pipeline.
//
// Design guarantees:
// • Concurrency is capped at config.AI_ANALYSIS_INDIVIDUAL_MAX_CONCURRENT.
// • A flat Set<messageId> de-duplicates so the same message can't be
// in-flight twice (Discord snowflakes are globally unique, but be safe).
// • A Map<conversationKey, count> lets the recovery worker skip conversations
// that already have individual work in progress (#4 fix).
// • A separate circuit breaker prevents a cascade of individual failures
// from hammering a down/rate-limited LLM endpoint (#1+#5 fix).
// ---------------------------------------------------------------------------
/** IDs currently being processed one-by-one. */
const individualInFlight = new Set<string>();
/**
* Per-conversation count of in-flight individual messages.
* Used by the recovery worker to avoid re-scheduling a conversation that
* already has individual fallback work running for it.
*/
const individualInFlightByConversation = new Map<string, number>();
/** Counter for observability. */
let activeIndividualRequests = 0;
// Individual fallback circuit breaker (independent of batch CB)
let individualConsecutiveErrors = 0;
let individualCooldownUntil = 0;
const INDIVIDUAL_COOLDOWN_MS = 30000;
// ---------------------------------------------------------------------------
// Piscina worker pool (batch path only)
// ---------------------------------------------------------------------------
function getAnalysisWorkerUrl(): URL {
const candidates = [
new URL("./aiAnalysisWorker.js", import.meta.url),
new URL("../aiAnalysisWorker.js", import.meta.url),
new URL("./aiAnalysisWorker.ts", import.meta.url),
];
for (const candidate of candidates) {
if (existsSync(fileURLToPath(candidate))) {
return candidate;
}
}
return candidates[2];
}
const workerPool = new Piscina({
filename: fileURLToPath(getAnalysisWorkerUrl()),
execArgv: process.execArgv,
});
interface AnalysisWorkerResponse {
ok: boolean;
conversationKey: string;
rows: MessageRecord[];
error?: string;
}
// ---------------------------------------------------------------------------
// Exported helpers
// ---------------------------------------------------------------------------
/**
* Gets the conversation key for a message (thread_id or channel_id).
*/
export function getConversationKey(message: MessageRecord): string {
return message.thread_id || message.channel_id;
}
/**
* Picks a batch of messages within a token budget.
* `tokensPerMessage` accounts for JSON structure overhead around each entry.
*/
export function pickBatchWithinBudget(
messages: MessageRecord[],
maxTokens: number,
tokensPerMessage: number,
): MessageRecord[] {
const batch: MessageRecord[] = [];
let usedTokens = 0;
for (const msg of messages) {
const formatted = formatMessageForPrompt(msg, "target");
const msgTokens = estimateTokens(formatted) + tokensPerMessage;
if (usedTokens + msgTokens <= maxTokens) {
batch.push(msg);
usedTokens += msgTokens;
}
}
return batch;
}
// ---------------------------------------------------------------------------
// Conversation lock helpers
// ---------------------------------------------------------------------------
function isConversationProcessingLocked(conversationKey: string): boolean {
const startedAt = conversationProcessing.get(conversationKey);
// FIX #7: use configurable timeout that exceeds (LLM timeout × max retries).
// Old hardcoded value was 30 000 ms — shorter than a single LLM call under retries.
return Boolean(
startedAt &&
Date.now() - startedAt < config.AI_ANALYSIS_PROCESSING_TIMEOUT_MS,
);
}
// ---------------------------------------------------------------------------
// Individual fallback pipeline
// ---------------------------------------------------------------------------
/**
* Processes a single message directly in the main process (no IPC/worker
* pool overhead). Never called from the batch path.
*
* FIX #1+#5: Increments the individual circuit breaker on failure so a
* sustained outage stops hammering the LLM endpoint.
*
* Infinite-loop prevention: if the LLM consistently drops the single target
* message across all retries (analysis_incomplete), we write a terminal flag
* 'individual_analysis_exhausted' to DB instead of 'analysis_incomplete'.
* The recovery worker only queries for 'analysis_incomplete', so exhausted
* messages are permanently excluded from the reprocessing loop.
* Transient failures (network/parse/DB) are NOT written as exhausted — they
* stay as 'analysis_incomplete' so the circuit-breaker-throttled recovery
* cycle can retry them later.
*/
async function processIndividualFallback(
message: MessageRecord,
): Promise<void> {
const { id: messageId } = message;
const conversationKey = getConversationKey(message);
activeIndividualRequests++;
// Increment per-conversation counter so the recovery worker can see it.
individualInFlightByConversation.set(
conversationKey,
(individualInFlightByConversation.get(conversationKey) ?? 0) + 1,
);
// Track whether all retries were exhausted specifically because the LLM
// consistently returned no result for this message (vs. a transient error).
let exhaustedOnIncomplete = false;
try {
const contextBefore = await getConversationContextBefore({
channelId: message.channel_id,
threadId: message.thread_id,
beforeCreatedAt: message.created_at,
limit: config.AI_ANALYSIS_CONTEXT_MESSAGE_LIMIT,
});
const contextLines = buildConversationContext({
contextBefore,
targets: [message],
maxTokens: config.AI_ANALYSIS_MAX_CONTEXT_TOKENS,
});
const contextIds = contextBefore.map((m) => m.id);
const attachments = await getAttachmentsForMessages([
messageId,
...contextIds,
]);
const analysisResult = await retryWithBackoff(
async () => {
try {
const result = await runModerationAnalysis({
targets: [message],
contextText: contextLines.join("\n"),
attachments,
});
// If the LLM still dropped our only target, convert to a retryable
// throw so backoff kicks in. Track this so the catch block can
// distinguish it from a transient network/parse failure.
const stillIncomplete = result.results.some((r) =>
r.flags.includes("analysis_incomplete"),
);
if (stillIncomplete) {
exhaustedOnIncomplete = true;
throw new Error(
`LLM returned no result for single-target message ${messageId} — will retry with backoff`,
);
}
// Got a real result — clear the incomplete flag.
exhaustedOnIncomplete = false;
return result;
} catch (err: any) {
// Propagate AbortError so outer retry is immediately cancelled on 429.
if (err instanceof AbortError) {
throw err;
}
if (
err?.status === 429 ||
err?.status === 401 ||
err?.status === 403
) {
throw new AbortError(err);
}
throw err;
}
},
{
retries: 2,
minTimeout: 2000,
maxTimeout: 15000,
logger,
},
);
const updates = analysisResult.results.map((r) => ({
messageId: r.messageId,
result: {
status: r.status,
flags: JSON.stringify(r.flags),
score: r.score,
raw: JSON.stringify(analysisResult.raw),
analysis: r.analysis,
categories: r.categories,
severity: r.severity,
confidence: r.confidence,
recommendedAction: r.recommendedAction,
policyVersion: r.policyVersion,
evidence: r.evidence,
analyzedAt: Date.now(),
error: null,
},
}));
const rows = await updateMessagesAIAnalysisBulk(updates);
for (const row of rows) {
getModerationBroadcaster()?.messageAnalyzed(row);
scheduleAutoDelete(row);
}
// Reset individual CB on success.
individualConsecutiveErrors = 0;
logger.info(
{ messageId, status: analysisResult.results[0]?.status },
"Individual fallback analysis complete",
);
} catch (error) {
// FIX #5: individual failures now feed their own circuit breaker.
individualConsecutiveErrors++;
if (
individualConsecutiveErrors >= config.AI_ANALYSIS_INDIVIDUAL_CB_THRESHOLD
) {
individualCooldownUntil = Date.now() + INDIVIDUAL_COOLDOWN_MS;
logger.warn(
{
threshold: config.AI_ANALYSIS_INDIVIDUAL_CB_THRESHOLD,
cooldownUntil: new Date(individualCooldownUntil).toISOString(),
},
"Individual fallback circuit breaker triggered",
);
}
lastError = error instanceof Error ? error.message : String(error);
// Infinite-loop prevention: if all retries were exhausted because the LLM
// consistently dropped this specific message (not a transient error),
// overwrite the DB entry with a terminal flag that the recovery query
// does NOT match. This permanently removes it from the recovery loop
// while keeping it visible as an error in the dashboard.
if (exhaustedOnIncomplete) {
await updateMessagesAIAnalysisBulk([
{
messageId,
result: {
status: "error",
flags: JSON.stringify(["individual_analysis_exhausted"]),
score: 0,
raw: null,
analysis:
"Individual fallback exhausted all retries: LLM consistently dropped this message even in single-target mode",
categories: ["individual_analysis_exhausted"],
severity: "none",
confidence: 0,
recommendedAction: "review",
policyVersion: "default-2026-05-30",
evidence: [],
analyzedAt: Date.now(),
error: lastError,
},
},
]).catch((dbErr) => {
logger.error(
{ messageId, error: String(dbErr) },
"Failed to write terminal exhausted status — message may re-enter recovery loop",
);
});
logger.warn(
{ messageId },
"Individual fallback exhausted — marked as individual_analysis_exhausted to stop recovery loop",
);
} else {
// Transient failure (network/parse/DB): do NOT write terminal status.
// Message stays as error/analysis_incomplete in DB and will be retried
// by the recovery worker, subject to the individual circuit breaker.
logger.error(
{
messageId,
error: lastError,
stack: error instanceof Error ? error.stack : undefined,
},
"Individual fallback analysis failed (transient) — will be retried by recovery worker",
);
}
} finally {
activeIndividualRequests--;
individualInFlight.delete(messageId);
// Decrement per-conversation counter; remove key when it hits zero.
const prev = individualInFlightByConversation.get(conversationKey) ?? 1;
if (prev <= 1) {
individualInFlightByConversation.delete(conversationKey);
} else {
individualInFlightByConversation.set(conversationKey, prev - 1);
}
}
}
/**
* Fans out message records to the individual fallback queue.
*
* FIX #1: Checks concurrency cap before admitting new work.
* FIX #5: Checks individual circuit breaker before admitting new work.
* Messages that cannot be admitted remain as `error/analysis_incomplete` in
* the DB and will be picked up by the recovery worker on the next interval.
*/
function enqueueIndividualFallbacks(messages: MessageRecord[]): void {
// FIX #5: Honour the individual circuit breaker.
if (Date.now() < individualCooldownUntil) {
logger.warn(
{
until: new Date(individualCooldownUntil).toISOString(),
skipped: messages.length,
},
"Individual fallback circuit breaker active — messages will be recovered later",
);
return;
}
const newMessages = messages.filter((m) => !individualInFlight.has(m.id));
if (newMessages.length === 0) return;
// FIX #1: Enforce concurrency cap.
const availableSlots =
config.AI_ANALYSIS_INDIVIDUAL_MAX_CONCURRENT - individualInFlight.size;
if (availableSlots <= 0) {
logger.warn(
{
cap: config.AI_ANALYSIS_INDIVIDUAL_MAX_CONCURRENT,
inFlight: individualInFlight.size,
skipped: newMessages.length,
},
"Individual fallback concurrency cap reached — messages will be recovered by recovery worker",
);
return;
}
const toProcess = newMessages.slice(0, availableSlots);
const skipped = newMessages.length - toProcess.length;
logger.info(
{
count: toProcess.length,
skipped,
messageIds: toProcess.map((m) => m.id),
},
"Enqueueing individual fallback analysis for batch-incomplete messages",
);
for (const msg of toProcess) {
individualInFlight.add(msg.id);
// Fire-and-forget: processIndividualFallback handles all errors internally.
processIndividualFallback(msg).catch((err) => {
// Belt-and-suspenders guard — should never reach here.
logger.error(
{ messageId: msg.id, error: String(err) },
"Unexpected uncaught error escaping processIndividualFallback",
);
individualInFlight.delete(msg.id);
const ck = getConversationKey(msg);
const prev = individualInFlightByConversation.get(ck) ?? 1;
if (prev <= 1) {
individualInFlightByConversation.delete(ck);
} else {
individualInFlightByConversation.set(ck, prev - 1);
}
});
}
}
// ---------------------------------------------------------------------------
// Batch pipeline
// ---------------------------------------------------------------------------
async function processBatch(
conversationKey: string,
messages: MessageRecord[],
): Promise<void> {
if (messages.length === 0) return;
if (Date.now() < globalCooldownUntil) {
return;
}
activeRequests++;
let shouldScheduleNext = false;
const processingStartedAt = Date.now();
conversationProcessing.set(conversationKey, processingStartedAt);
try {
const result = (await workerPool.run({
conversationKey,
messages,
})) as AnalysisWorkerResponse;
for (const row of result.rows) {
getModerationBroadcaster()?.messageAnalyzed(row);
scheduleAutoDelete(row);
}
if (!result.ok) {
consecutiveErrors++;
if (consecutiveErrors >= MAX_CONSECUTIVE_ERRORS) {
globalCooldownUntil = Date.now() + 60000;
logger.warn(
"Global circuit breaker triggered due to consecutive errors",
);
}
// Batch failed entirely — fall back all messages to individual queue
// so no message is permanently lost behind a cooldown.
logger.warn(
{
conversationKey,
messageCount: messages.length,
error: result.error,
},
"Batch failed entirely — routing all messages to individual fallback queue",
);
enqueueIndividualFallbacks(messages);
lastError = result.error ?? "Analysis worker failed";
conversationErrorCooldown.set(
conversationKey,
Date.now() + config.AI_ANALYSIS_ERROR_COOLDOWN_MS,
);
logger.error(
{
conversationKey,
error: lastError,
messageCount: messages.length,
messageIds: messages.map((m) => m.id),
cooldownUntil: new Date(
Date.now() + config.AI_ANALYSIS_ERROR_COOLDOWN_MS,
).toISOString(),
timestamp: new Date().toISOString(),
},
"Batch analysis failed, will retry after cooldown",
);
return;
}
// Batch succeeded — but check for messages the LLM silently dropped.
// Rows with flag "analysis_incomplete" were produced by parseModerationResponse
// as synthetic errors; they must be re-processed individually.
const incompleteMessages = messages.filter((msg) => {
const row = result.rows.find((r) => r.id === msg.id);
if (!row) {
// The DB update row is missing entirely — treat as incomplete.
return true;
}
const flags: string[] = (() => {
try {
return JSON.parse(row.ai_moderation_flags ?? "[]") as string[];
} catch {
return [];
}
})();
return row.ai_status === "error" && flags.includes("analysis_incomplete");
});
if (incompleteMessages.length > 0) {
logger.warn(
{
conversationKey,
incompleteCount: incompleteMessages.length,
incompleteIds: incompleteMessages.map((m) => m.id),
totalBatchSize: messages.length,
},
"Batch returned incomplete results — fanning out to individual fallback queue",
);
enqueueIndividualFallbacks(incompleteMessages);
}
consecutiveErrors = 0; // Reset batch circuit breaker
conversationErrorCooldown.delete(conversationKey);
shouldScheduleNext = true;
} catch (error) {
consecutiveErrors++;
if (consecutiveErrors >= MAX_CONSECUTIVE_ERRORS) {
globalCooldownUntil = Date.now() + 60000;
logger.warn("Global circuit breaker triggered due to consecutive errors");
}
// Unhandled exception — route everything to individual fallback.
logger.warn(
{ conversationKey, messageCount: messages.length },
"Batch threw exception — routing all messages to individual fallback queue",
);
enqueueIndividualFallbacks(messages);
lastError = error instanceof Error ? error.message : String(error);
const errorStack = error instanceof Error ? error.stack : undefined;
conversationErrorCooldown.set(
conversationKey,
Date.now() + config.AI_ANALYSIS_ERROR_COOLDOWN_MS,
);
logger.error(
{
conversationKey,
error: lastError,
stack: errorStack,
messageCount: messages.length,
messageIds: messages.map((m) => m.id),
cooldownUntil: new Date(
Date.now() + config.AI_ANALYSIS_ERROR_COOLDOWN_MS,
).toISOString(),
timestamp: new Date().toISOString(),
},
"Analysis worker failed, will retry after cooldown",
);
} finally {
activeRequests--;
if (conversationProcessing.get(conversationKey) === processingStartedAt) {
conversationProcessing.delete(conversationKey);
}
if (shouldScheduleNext) {
setImmediate(() => scheduleConversationAnalysis(conversationKey));
}
}
}
// ---------------------------------------------------------------------------
// Scheduling
// ---------------------------------------------------------------------------
/**
* Schedules a debounced analysis run for a conversation.
*
* FIX #3: The async work inside setTimeout is now wrapped in an explicit
* .catch() so DB errors don't produce unhandled promise rejections.
* FIX #6: Calls pickBatchWithinBudget after fetching messages so token budget
* is respected before handing the batch to the LLM.
*/
function scheduleConversationAnalysis(conversationKey: string): void {
if (isConversationProcessingLocked(conversationKey)) {
return;
}
const convoCooldown = conversationErrorCooldown.get(conversationKey) || 0;
const activeCooldown = Math.max(convoCooldown, globalCooldownUntil);
if (activeCooldown && Date.now() < activeCooldown) {
if (!conversationDebounceTimers.has(conversationKey)) {
const remaining = activeCooldown - Date.now();
const timer = setTimeout(() => {
conversationDebounceTimers.delete(conversationKey);
scheduleConversationAnalysis(conversationKey);
}, remaining + 500);
conversationDebounceTimers.set(conversationKey, timer);
}
return;
}
const existingTimer = conversationDebounceTimers.get(conversationKey);
if (existingTimer) {
clearTimeout(existingTimer);
}
const timer = setTimeout(() => {
conversationDebounceTimers.delete(conversationKey);
// FIX #3: explicit .catch() — no async arrow function to avoid unhandled rejection.
getPendingMessagesByConversation(
conversationKey,
config.AI_ANALYSIS_MAX_BATCH_SIZE,
)
.then((messages) => {
if (messages.length === 0) return;
// FIX #6: trim to token budget before sending to LLM.
// 50 tokens overhead accounts for JSON structure + id/username fields.
let trimmed = pickBatchWithinBudget(
messages,
config.AI_ANALYSIS_MAX_TARGET_TOKENS,
50,
);
// FIX #10: if every message individually exceeds the token budget,
// pickBatchWithinBudget returns [] — which would leave them permanently
// stuck as `pending`. Fall back to the first message alone so at
// least one makes progress; the rest will be processed in later ticks.
if (trimmed.length === 0 && messages.length > 0) {
trimmed = messages.slice(0, 1);
logger.warn(
{
conversationKey,
messageId: messages[0]?.id,
tokenBudget: config.AI_ANALYSIS_MAX_TARGET_TOKENS,
},
"All messages exceed token budget — processing first message alone to avoid stuck-pending deadlock",
);
}
return processBatch(conversationKey, trimmed);
})
.catch((err) => {
logger.error(
{
conversationKey,
error: err instanceof Error ? err.message : String(err),
},
"Failed to fetch or dispatch pending messages for scheduled analysis",
);
});
}, config.AI_ANALYSIS_DEBOUNCE_MS);
conversationDebounceTimers.set(conversationKey, timer);
}
// ---------------------------------------------------------------------------
// Public API
// ---------------------------------------------------------------------------
/**
* Queues a message for analysis (debounced by conversation).
*/
export async function queueMessageAnalysis(messageId: string): Promise<void> {
if (!config.AI_ANALYSIS_ENABLED) return;
try {
const message = await getMessageById(messageId);
if (!message) {
logger.warn({ messageId }, "Message not found for analysis queue");
return;
}
queueConversationAnalysis(getConversationKey(message));
} catch (error) {
logger.error(
{
messageId,
error: error instanceof Error ? error.message : String(error),
},
"Failed to queue message for analysis",
);
}
}
/**
* Queues a conversation for analysis (debounced).
*/
export function queueConversationAnalysis(conversationKey: string): void {
if (!config.AI_ANALYSIS_ENABLED) return;
scheduleConversationAnalysis(conversationKey);
}
/**
* Returns current status of both the batch and individual fallback queues.
*/
export function getAnalysisQueueStatus(): AnalysisQueueStatus {
return {
queuedConversations: conversationDebounceTimers.size,
activeRequests,
activeIndividualRequests,
individualInFlightCount: individualInFlight.size,
individualCircuitBreakerActive: Date.now() < individualCooldownUntil,
lastError,
};
}
/**
* Starts the periodic recovery worker.
*
* FIX #4: Now also recovers messages stuck in `error/analysis_incomplete`
* state (not just `pending`), and skips conversations that already have
* individual fallback work in progress to avoid DB last-write-wins races.
*/
export function startPendingAIAnalysisWorker(client?: Client): void {
moderationClient = client;
if (!config.AI_ANALYSIS_ENABLED) return;
setInterval(() => {
// FIX #3 pattern: no async arrow — chain promises explicitly.
Promise.all([
getPendingConversationKeys(100),
getConversationKeysWithIncompleteAnalysis(50),
])
.then(([pendingKeys, incompleteKeys]) => {
const now = Date.now();
// FIX #9: Prune stale entries from state maps to prevent unbounded
// memory growth from channels/threads that are no longer active.
for (const [key, expiry] of conversationErrorCooldown) {
if (now >= expiry) conversationErrorCooldown.delete(key);
}
for (const [key, startedAt] of conversationProcessing) {
if (now - startedAt >= config.AI_ANALYSIS_PROCESSING_TIMEOUT_MS) {
conversationProcessing.delete(key);
}
}
// FIX #8: Build a set of keys already targeted for individual recovery
// so the batch loop below skips them, preventing a race where batch
// scheduling and individual scheduling collide on the same conversation.
const incompleteKeySet = new Set(incompleteKeys);
// --- Batch recovery for `pending` messages ---
for (const key of pendingKeys) {
if (conversationDebounceTimers.has(key)) continue;
if (isConversationProcessingLocked(key)) continue;
// FIX #4: skip if individual fallback already running for this conversation.
if (individualInFlightByConversation.has(key)) continue;
// FIX #8: skip if this conversation also needs individual recovery
// (batch processing would conflict with in-flight individual work).
if (incompleteKeySet.has(key)) continue;
const cooldownUntil = conversationErrorCooldown.get(key);
if (cooldownUntil && now < cooldownUntil) continue;
scheduleConversationAnalysis(key);
}
// --- Individual recovery for `error/analysis_incomplete` messages ---
// Circuit breaker check: no point iterating if individual CB is active.
if (now >= individualCooldownUntil) {
const promises: Promise<void>[] = [];
for (const key of incompleteKeys) {
// Skip if individual work is already running for this conversation.
if (individualInFlightByConversation.has(key)) continue;
// Skip if batch processing is running (it will fan-out if it finds more incomplete).
if (isConversationProcessingLocked(key)) continue;
promises.push(
getIncompleteMessagesByConversation(
key,
config.AI_ANALYSIS_INDIVIDUAL_MAX_CONCURRENT,
)
.then((msgs) => {
if (msgs.length > 0) {
enqueueIndividualFallbacks(msgs);
}
})
.catch((err) => {
logger.error(
{ key, error: String(err) },
"Failed to fetch incomplete messages for recovery",
);
}),
);
}
// Errors are handled per-key; return the combined promise for observability.
return Promise.all(promises);
}
})
.catch((err) => {
logger.error(
{ error: err instanceof Error ? err.message : String(err) },
"Pending AI analysis recovery worker failed",
);
});
}, config.AI_ANALYSIS_RECOVERY_INTERVAL_MS);
}