fix(predictions): cooldown fallback cascade + circuit breaker tuning
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- Add 4-level fallback when AI circuit breaker fires cooldown:
  1) In-memory cache (10min TTL)
  2) DB stored prediction (no TTL filter)
  3) DB cached prediction (with model version check)
  4) Wait out cooldown + retry once (max 20s wait)
- Raise circuit breaker threshold from 3 to 5 consecutive failures
- Reduce cooldown duration from 30s to 15s for faster recovery
- Add extractCooldownMs helper to parse remaining ms from error detail
This commit is contained in:
2026-05-05 20:11:19 +03:00
parent 5645b38f20
commit f32badbd8f
2 changed files with 63 additions and 2 deletions
+2 -2
View File
@@ -69,8 +69,8 @@ export class AiEngineClient {
this.defaultTimeoutMs = options.timeoutMs ?? 30000;
this.maxRetries = options.maxRetries ?? 2;
this.retryDelayMs = options.retryDelayMs ?? 750;
this.circuitBreakerThreshold = options.circuitBreakerThreshold ?? 3;
this.circuitBreakerCooldownMs = options.circuitBreakerCooldownMs ?? 30000;
this.circuitBreakerThreshold = options.circuitBreakerThreshold ?? 5;
this.circuitBreakerCooldownMs = options.circuitBreakerCooldownMs ?? 15000;
this.axiosClient = axios.create({
baseURL: options.baseUrl,
@@ -246,10 +246,21 @@ export class PredictionsService implements OnModuleInit, OnModuleDestroy {
const status = requestError.status;
const detail = requestError.detail || requestError.message;
// ── Cooldown fallback cascade: memCache → DB stored → DB cached → wait & retry ──
if (
status === HttpStatus.SERVICE_UNAVAILABLE &&
this.hasCooldown(detail)
) {
// 1) In-memory cache (10min TTL)
const memCached = this.predictionMemCache.get(matchId);
if (memCached && Date.now() - memCached.timestamp < 10 * 60 * 1000) {
this.logger.warn(
`AI Engine cooldown for ${matchId}; returning mem-cached prediction`,
);
return memCached.payload;
}
// 2) DB stored prediction (no TTL filter)
const storedPrediction = await this.getStoredPrediction(matchId);
if (storedPrediction) {
this.logger.warn(
@@ -257,6 +268,43 @@ export class PredictionsService implements OnModuleInit, OnModuleDestroy {
);
return this.enrichPredictionResponse(storedPrediction, matchContext);
}
// 3) DB cached prediction (with model version check)
const cachedPrediction = await this.getCachedPrediction(matchId);
if (cachedPrediction) {
this.logger.warn(
`AI Engine cooldown for ${matchId}; returning cached prediction`,
);
return this.enrichPredictionResponse(cachedPrediction, matchContext);
}
// 4) No cached data at all — wait out cooldown and retry once
const cooldownMs = this.extractCooldownMs(detail);
if (cooldownMs > 0 && cooldownMs <= 20000) {
this.logger.warn(
`AI Engine cooldown for ${matchId}; no cached data — waiting ${cooldownMs}ms and retrying...`,
);
await new Promise((resolve) => setTimeout(resolve, cooldownMs + 500));
try {
const retryResponse =
await this.aiEngineClient.post<MatchPredictionDto>(
`/v20plus/analyze/${matchId}`,
{ simulate: true, is_simulation: true, pre_match_only: true },
);
const retryPrediction = this.enrichPredictionResponse(
retryResponse.data,
matchContext,
);
await this.recordPredictionRun(matchId, retryResponse.data);
await this.cachePrediction(matchId, retryPrediction);
return retryPrediction;
} catch (retryErr: unknown) {
this.logger.error(
`AI Engine retry after cooldown also failed for ${matchId}`,
);
// Fall through to error handling below
}
}
}
this.logger.error(
@@ -1243,6 +1291,19 @@ export class PredictionsService implements OnModuleInit, OnModuleDestroy {
return false;
}
private extractCooldownMs(detail: unknown): number {
if (detail && typeof detail === "object" && "cooldownRemainingMs" in detail) {
return Number((detail as Record<string, unknown>).cooldownRemainingMs) || 0;
}
if (typeof detail === "string") {
const match = detail.match(/cooldownRemainingMs[":\s]+(\d+)/);
return match ? Number(match[1]) : 0;
}
return 0;
}
private async ensureSmartCouponDataReady(matchIds: string[]): Promise<void> {
const uniqueMatchIds = [...new Set(matchIds.filter((id) => !!id))];
if (uniqueMatchIds.length === 0) {