claude-flow
Version:
Ruflo - Enterprise AI agent orchestration for Claude Code. Deploy 60+ specialized agents in coordinated swarms with self-learning, fault-tolerant consensus, vector memory, and MCP integration
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text/typescript
import type { TelemetryReading, AnomalyDetection } from '../entities/index.js';
import type { AnomalyDetectionService, TelemetryBaseline } from './anomaly-detection-service.js';
export interface TelemetryIngestionDeps {
queryDeviceStore: (
deviceId: string,
vector: number[],
k: number,
) => Promise<Array<{ id: number | string; distance: number; metadata?: Record<string, unknown> }>>;
getStoreStatus: (deviceId: string) => Promise<{ total_vectors: number; dimension: number }>;
}
export interface IngestionResult {
deviceId: string;
readingsProcessed: number;
anomaliesDetected: number;
anomalies: AnomalyDetection[];
baseline?: TelemetryBaseline;
}
export class TelemetryIngestionService {
constructor(
private readonly deps: TelemetryIngestionDeps,
private readonly anomalyDetector: AnomalyDetectionService,
) {}
/**
* Process a batch of telemetry readings: run anomaly detection on each,
* and return the results.
*/
processBatch(deviceId: string, readings: TelemetryReading[]): IngestionResult {
const anomalies: AnomalyDetection[] = [];
for (const reading of readings) {
const detection = this.anomalyDetector.detect(reading);
if (this.anomalyDetector.isAnomalous(detection)) {
anomalies.push(detection);
}
}
return {
deviceId,
readingsProcessed: readings.length,
anomaliesDetected: anomalies.length,
anomalies,
baseline: this.anomalyDetector.getBaseline(deviceId),
};
}
/**
* Compute or refresh the baseline for a device from its recent readings.
*/
refreshBaseline(deviceId: string, readings: TelemetryReading[]): TelemetryBaseline {
return this.anomalyDetector.computeBaseline(deviceId, readings);
}
/** Get the current baseline for a device. */
getBaseline(deviceId: string): TelemetryBaseline | undefined {
return this.anomalyDetector.getBaseline(deviceId);
}
}