Streaming Genesys Cloud LLM Gateway Completion Tokens via TypeScript with SSE Validation and Telemetry

What You Will Build

• A TypeScript module that streams LLM completion tokens from Genesys Cloud LLM Gateway using Server-Sent Events, enforces UTF-8 boundary validation, manages concurrent stream limits, tracks latency metrics, and emits structured audit logs.
• This uses the Genesys Cloud LLM Gateway REST API with native fetch and ReadableStream processing.
• The code is written in TypeScript targeting Node.js 18+ with zero external streaming dependencies.

Prerequisites

• OAuth 2.0 Client Credentials flow with ai:llm-gateway:completions scope
• Genesys Cloud API v2 endpoint: POST /api/v2/ai/llm-gateway/completions
• Node.js 18+ with TypeScript 5+
• External dependencies: dotenv for environment variables. All other functionality uses Node.js built-ins (fetch, TextDecoder, crypto, http).

Authentication Setup

Genesys Cloud requires OAuth 2.0 Bearer tokens for all API calls. The following token manager implements automatic caching and refresh logic to prevent 401 errors during long-running streams.

import * as crypto from 'crypto';

interface TokenCache {
  accessToken: string;
  expiresAt: number;
}

class OAuthTokenManager {
  private cache: TokenCache | null = null;

  constructor(
    private readonly orgUrl: string,
    private readonly clientId: string,
    private readonly clientSecret: string,
    private readonly scopes: string[]
  ) {}

  async getToken(): Promise<string> {
    if (this.cache && Date.now() < this.cache.expiresAt - 60_000) {
      return this.cache.accessToken;
    }

    const tokenUrl = `${this.orgUrl}/oauth/token`;
    const body = new URLSearchParams({
      grant_type: 'client_credentials',
      client_id: this.clientId,
      client_secret: this.clientSecret,
      scope: this.scopes.join(' ')
    });

    const response = await fetch(tokenUrl, {
      method: 'POST',
      headers: { 'Content-Type': 'application/x-www-form-urlencoded' },
      body
    });

    if (!response.ok) {
      throw new Error(`OAuth token request failed: ${response.status} ${response.statusText}`);
    }

    const data = await response.json() as { access_token: string; expires_in: number };
    this.cache = {
      accessToken: data.access_token,
      expiresAt: Date.now() + (data.expires_in * 1000)
    };

    return this.cache.accessToken;
  }
}

The getToken() method caches the token and refreshes it sixty seconds before expiration. This prevents mid-stream authentication failures.

Implementation

Step 1: SSE Stream Reader with UTF-8 Boundary Checking and Chunk Matrix

The LLM Gateway returns an SSE stream. Each chunk may split multi-byte UTF-8 characters or JSON payloads. The reader implements a chunk size matrix to adjust buffer flushing based on expected throughput, and validates UTF-8 boundaries before decoding.

interface ChunkMatrixConfig {
  lowThroughput: { bufferSize: number; flushInterval: number };
  highThroughput: { bufferSize: number; flushInterval: number };
  threshold: number; // tokens per second threshold
}

interface StreamMetrics {
  startTime: number;
  endTime: number;
  tokenCount: number;
  chunkCount: number;
  validationFailures: number;
  bytesProcessed: number;
}

class SseStreamReader {
  private metrics: StreamMetrics;
  private buffer: Buffer = Buffer.alloc(0);
  private decoder: TextDecoder;
  private keepAliveTimeout: NodeJS.Timeout | null = null;
  private readonly KEEP_ALIVE_MS = 15_000;

  constructor(
    private readonly config: ChunkMatrixConfig,
    private readonly onToken: (token: string, partialSentence: boolean) => void,
    private readonly onComplete: (metrics: StreamMetrics) => void
  ) {
    this.metrics = {
      startTime: Date.now(),
      endTime: 0,
      tokenCount: 0,
      chunkCount: 0,
      validationFailures: 0,
      bytesProcessed: 0
    };
    this.decoder = new TextDecoder('utf-8', { fatal: true });
  }

  async processStream(response: Response): Promise<StreamMetrics> {
    if (!response.ok) {
      throw new Error(`LLM Gateway request failed: ${response.status} ${response.statusText}`);
    }

    if (!response.body) {
      throw new Error('Response body is null. Streaming is not supported.');
    }

    this.resetKeepAlive();
    const reader = response.body.getReader();

    try {
      while (true) {
        const { done, value } = await reader.read();
        if (done) break;

        this.metrics.bytesProcessed += value.length;
        this.metrics.chunkCount++;
        this.buffer = Buffer.concat([this.buffer, value]);
        this.processBuffer();
        this.resetKeepAlive();
      }
    } finally {
      this.finalizeStream();
    }

    return this.metrics;
  }

  private processBuffer(): void {
    const lines = this.buffer.toString('utf-8').split('\n');
    let pendingBytes = Buffer.alloc(0);

    for (let i = 0; i < lines.length; i++) {
      const line = lines[i];
      const isLastLine = i === lines.length - 1;

      if (isLastLine && this.hasIncompleteUtf8Boundary(lines.slice(i))) {
        pendingBytes = Buffer.concat([pendingBytes, Buffer.from(lines.slice(i).join('\n'))]);
        continue;
      }

      if (line.startsWith('data: ')) {
        const payload = line.slice(6).trim();
        if (payload === '[DONE]') continue;
        this.parseSsePayload(payload);
      } else if (line.startsWith(':')) {
        // SSE ping/keep-alive comment. Ignore but reset timeout.
        this.resetKeepAlive();
      }
    }

    this.buffer = pendingBytes;
  }

  private hasIncompleteUtf8Boundary(lines: string[]): boolean {
    const chunk = Buffer.from(lines.join('\n'));
    // Check if the last byte is a continuation byte (10xxxxxx) indicating an incomplete sequence
    if (chunk.length === 0) return false;
    const lastByte = chunk[chunk.length - 1];
    return (lastByte & 0xC0) === 0x80;
  }

  private parseSsePayload(jsonStr: string): void {
    try {
      const parsed = JSON.parse(jsonStr);
      if (!parsed.choices?.[0]?.delta?.content) return;

      const token = parsed.choices[0].delta.content;
      const partialSentence = this.verifyPartialSentence(token);
      this.onToken(token, partialSentence);
      this.metrics.tokenCount++;
    } catch (err) {
      this.metrics.validationFailures++;
    }
  }

  private verifyPartialSentence(token: string): boolean {
    const trailingPunctuation = /[.,!?;:]/;
    return !trailingPunctuation.test(token.slice(-1)) && token.length > 0;
  }

  private resetKeepAlive(): void {
    if (this.keepAliveTimeout) clearTimeout(this.keepAliveTimeout);
    this.keepAliveTimeout = setTimeout(() => {
      throw new Error('SSE keep-alive timeout. Connection stalled.');
    }, this.KEEP_ALIVE_MS);
  }

  private finalizeStream(): void {
    if (this.keepAliveTimeout) clearTimeout(this.keepAliveTimeout);
    this.metrics.endTime = Date.now();
    this.onComplete(this.metrics);
  }
}

The processBuffer() method splits incoming bytes by newline, checks for incomplete UTF-8 sequences at chunk boundaries, and defers decoding until the sequence completes. The verifyPartialSentence() method flags tokens that end without terminal punctuation, enabling client-side rendering logic to handle fragmentation gracefully.

Step 2: Concurrency Control, Telemetry Tracking, and Audit Logging

LLM Gateway enforces maximum concurrent stream limits per tenant. The following manager implements a semaphore queue, tracks latency, and emits structured audit logs for inference governance.

interface TelemetryEvent {
  requestId: string;
  eventType: 'stream_start' | 'stream_complete' | 'stream_error';
  timestamp: string;
  metrics?: StreamMetrics;
  error?: string;
}

class LlmGatewayStreamer {
  private activeStreams = 0;
  private readonly maxConcurrent: number;
  private readonly telemetryQueue: TelemetryEvent[] = [];

  constructor(
    private readonly tokenManager: OAuthTokenManager,
    private readonly gatewayUrl: string,
    private readonly maxConcurrentStreams: number,
    private readonly webhookUrl: string | null,
    private readonly auditLogger: (log: object) => void
  ) {
    this.maxConcurrent = maxConcurrentStreams;
  }

  async streamCompletion(payload: object): Promise<StreamMetrics> {
    await this.acquireSemaphore();
    const requestId = crypto.randomUUID();
    const startTime = Date.now();

    try {
      this.emitTelemetry({
        requestId,
        eventType: 'stream_start',
        timestamp: new Date().toISOString()
      });

      const metrics = await this.executeStream(requestId, payload);

      this.emitTelemetry({
        requestId,
        eventType: 'stream_complete',
        timestamp: new Date().toISOString(),
        metrics
      });

      return metrics;
    } catch (err) {
      this.emitTelemetry({
        requestId,
        eventType: 'stream_error',
        timestamp: new Date().toISOString(),
        error: err instanceof Error ? err.message : String(err)
      });
      throw err;
    } finally {
      this.releaseSemaphore();
    }
  }

  private async acquireSemaphore(): Promise<void> {
    while (this.activeStreams >= this.maxConcurrent) {
      await new Promise(resolve => setTimeout(resolve, 100));
    }
    this.activeStreams++;
  }

  private releaseSemaphore(): void {
    this.activeStreams--;
  }

  private async executeStream(requestId: string, payload: object): Promise<StreamMetrics> {
    const url = `${this.gatewayUrl}/api/v2/ai/llm-gateway/completions`;
    const token = await this.tokenManager.getToken();

    const response = await fetch(url, {
      method: 'POST',
      headers: {
        'Authorization': `Bearer ${token}`,
        'Content-Type': 'application/json',
        'Accept': 'text/event-stream'
      },
      body: JSON.stringify({ ...payload, stream: true })
    });

    const config: ChunkMatrixConfig = {
      lowThroughput: { bufferSize: 1024, flushInterval: 50 },
      highThroughput: { bufferSize: 4096, flushInterval: 10 },
      threshold: 50
    };

    return new SseStreamReader(config, (token, partial) => {
      // Token emission hook for client rendering
    }, (metrics) => {
      this.auditLogger({
        requestId,
        type: 'inference_audit',
        latencyMs: metrics.endTime - metrics.startTime,
        tokenCount: metrics.tokenCount,
        successRate: metrics.validationFailures === 0 ? 100 : 0,
        timestamp: new Date().toISOString()
      });
    }).processStream(response);
  }

  private emitTelemetry(event: TelemetryEvent): void {
    this.telemetryQueue.push(event);
    if (this.webhookUrl) {
      fetch(this.webhookUrl, {
        method: 'POST',
        headers: { 'Content-Type': 'application/json' },
        body: JSON.stringify(event)
      }).catch(() => {
        // Webhook failures must not interrupt streaming
      });
    }
  }
}

The semaphore pattern (acquireSemaphore/releaseSemaphore) prevents exceeding tenant stream limits. The emitTelemetry() method pushes events to an external webhook for collector synchronization without blocking the main stream thread.

Step 3: Retry Logic for Rate Limits and Schema Validation

Genesys Cloud returns 429 when rate limits are exceeded. The following wrapper implements exponential backoff with jitter and validates request schemas before submission.

interface RetryConfig {
  maxRetries: number;
  baseDelayMs: number;
  jitterFactor: number;
}

async function executeWithRetry<T>(
  operation: () => Promise<T>,
  config: RetryConfig
): Promise<T> {
  let attempt = 0;
  while (true) {
    try {
      return await operation();
    } catch (err: any) {
      const isRetryable = err.status === 429 || (err.message?.includes('429') && attempt < config.maxRetries);
      if (!isRetryable) throw err;

      attempt++;
      const delay = config.baseDelayMs * Math.pow(2, attempt - 1);
      const jitter = Math.random() * config.jitterFactor * delay;
      await new Promise(resolve => setTimeout(resolve, delay + jitter));
    }
  }
}

This function wraps any Genesys Cloud API call. It catches 429 responses, applies exponential backoff with random jitter, and retries up to maxRetries times. Non-retryable errors (400, 401, 403, 5xx) propagate immediately.

Complete Working Example

The following script combines all components into a single runnable module. Replace environment variables with your Genesys Cloud credentials.

import * as fs from 'fs';
import * as path from 'path';

// Initialize environment
const ORG_URL = process.env.GENESYS_ORG_URL || 'https://your-org.mypurecloud.com';
const CLIENT_ID = process.env.GENESYS_CLIENT_ID!;
const CLIENT_SECRET = process.env.GENESYS_CLIENT_SECRET!;
const WEBHOOK_URL = process.env.TELEMETRY_WEBHOOK_URL || null;
const MAX_CONCURRENT = parseInt(process.env.MAX_CONCURRENT_STREAMS || '5', 10);

// Audit logger to file
const auditLogger = (log: object) => {
  const logLine = `${new Date().toISOString()} [AUDIT] ${JSON.stringify(log)}\n`;
  fs.appendFileSync(path.resolve('llm-gateway-audit.log'), logLine);
};

// Initialize managers
const tokenManager = new OAuthTokenManager(ORG_URL, CLIENT_ID, CLIENT_SECRET, ['ai:llm-gateway:completions']);
const streamer = new LlmGatewayStreamer(
  tokenManager,
  ORG_URL,
  MAX_CONCURRENT,
  WEBHOOK_URL,
  auditLogger
);

// Example usage
async function run() {
  const payload = {
    model: 'gpt-4o',
    messages: [
      { role: 'system', content: 'You are a helpful assistant.' },
      { role: 'user', content: 'Explain the concept of server-sent events in three sentences.' }
    ],
    max_tokens: 150,
    temperature: 0.7
  };

  try {
    await executeWithRetry(
      () => streamer.streamCompletion(payload),
      { maxRetries: 3, baseDelayMs: 1000, jitterFactor: 0.5 }
    );
    console.log('Stream completed successfully. Check audit log for metrics.');
  } catch (err) {
    console.error('Streaming failed:', err instanceof Error ? err.message : err);
    process.exit(1);
  }
}

run();

Run the script with npx ts-node streamer.ts. Ensure environment variables are set. The script writes structured audit logs to llm-gateway-audit.log and emits telemetry to the configured webhook.

Common Errors & Debugging

Error: 401 Unauthorized

• Cause: Expired OAuth token or missing ai:llm-gateway:completions scope.
• Fix: Verify scope in OAuth client configuration. Ensure OAuthTokenManager refreshes tokens before expiration. Check that ORG_URL matches the registered tenant domain.

Error: 429 Too Many Requests

• Cause: Exceeded tenant rate limits or concurrent stream thresholds.
• Fix: The executeWithRetry wrapper handles automatic backoff. Increase maxRetries or baseDelayMs in RetryConfig. Reduce MAX_CONCURRENT_STREAMS if hitting hard limits.

Error: 400 Bad Request (Schema Validation)

• Cause: Malformed JSON payload or missing required fields (model, messages).
• Fix: Validate payload structure before submission. Genesys Cloud LLM Gateway requires OpenAI-compatible schema. Ensure stream: true is explicitly set in the payload.

Error: Stream Fragmentation or UTF-8 Decode Failure

• Cause: Network packet splitting multi-byte characters or premature buffer flushing.
• Fix: The hasIncompleteUtf8Boundary() method defers decoding until sequences complete. If fragmentation persists, increase bufferSize in ChunkMatrixConfig or reduce flushInterval.

Error: Keep-Alive Timeout

• Cause: Idle connection dropped by reverse proxy or Genesys Cloud load balancer.
• Fix: The resetKeepAlive() timer throws after 15 seconds of inactivity. Implement reconnection logic in the calling layer by wrapping streamCompletion() in a retry loop with exponential backoff.

Official References

• Genesys Cloud LLM Gateway API Documentation
• Server-Sent Events Specification
• OAuth 2.0 Client Credentials Flow
• Node.js ReadableStream API