ElevenLabs Reference Architecture

Overview

Production-ready architecture for ElevenLabs TTS/voice applications. Covers project

layout, service layers, caching, streaming, and multi-model orchestration. The full

code for each layer lives in references/ so this file stays a navigable map; drill

into a reference file when you need the exact implementation.

Prerequisites

• Understanding of layered architecture patterns
• ElevenLabs SDK knowledge (see elevenlabs-sdk-patterns)
• TypeScript project with async patterns
• Redis (optional, for distributed caching)
• Auth: an ElevenLabs API key exported as ELEVENLABSAPIKEY (read by the

config layer). This is the only ElevenLabs credential — your app's own request

auth (middleware/auth.ts) is separate and unrelated.

Instructions

Build the service in six layers. Each step below is the high-level move; the

verbatim code and diagrams are in the linked reference files.

Step 1: Lay out the project

Split the codebase into elevenlabs/ (client, config, models, errors, types),

services/ (tts, voice, audio, cache), api/ (routes + middleware), queue/, and

monitoring/. See the full project tree.

Step 2: Configuration layer

Define an environment-aware ElevenLabsConfig — dev uses the cheap/fast

elevenflashv25 and small output format; production uses elevenmultilingual_v2

at higher quality, more concurrency, and a larger cache. loadConfig() merges the

per-environment defaults with ELEVENLABSAPIKEY. Full interface and ENV_CONFIGS:

implementation walkthrough.

Step 3: TTS service layer

Wrap the SDK client in a TTSService that owns a singleton client and a p-queue

sized to maxConcurrency (this is what prevents 429s). generate() supports both

streaming and buffered convert, logs latency, and routes errors through

classifyError. generateLongText() splits on sentence boundaries under the 5000-char

limit to preserve prosody. Full class:

implementation walkthrough.

Step 4: Voice management service

A VoiceService over the client for list/clone/get-settings/update-settings/delete,

with category filtering (premade / cloned / generated). Full class:

implementation walkthrough.

Step 5: Wire the data flow

Requests flow Client → API layer → Cache/TTS/Voice services → queue → singleton SDK

client → ElevenLabs REST/WS endpoints. See the

data flow diagram.

Step 6: Health check composition

Compose a /health route that runs connectivity, quota, and cache checks with

Promise.allSettled, returning healthy / degraded / unhealthy (degraded once

quota exceeds 90%). Full function:

implementation walkthrough.

Every architectural choice (singleton client, p-queue, LRU-vs-Redis, sentence

splitting, environment-based model selection, HTTP-vs-WS streaming) and its rationale

is tabulated in the architecture decisions table.

Output

Applying this skill produces a layered service scaffold, not a single file:

• A directory tree matching the project structure.
• An environment-aware config module resolving dev/staging/production defaults.
• A TTSService (queued, retry-aware, streaming-capable) and a VoiceService.
• A /health route returning { status, services, timestamp } where status is

healthy, degraded, or unhealthy.

• At runtime, generate() returns a Buffer (or a ReadableStream when

streaming: true); generateLongText() returns Buffer[], one per chunk.

Error Handling

Examples

Generate speech through the service layer:

const tts = new TTSService();
const audio = await tts.generate("Hello from production.", {
  voiceId: "21m00Tcm4TlvDq8ikWAM",
});

Stream a long article with prosody-preserving chunking:

const chunks = await tts.generateLongText(longArticleText);
// chunks: Buffer[] — concatenate or pipe in order

For the complete, runnable layers behind these snippets — config, full TTSService,

VoiceService, and the /health composition — see the

implementation walkthrough. For the project tree,

data flow, and decision rationale, see architecture.md.

Resources

• ElevenLabs API Reference
• ElevenLabs SDK Source
• p-queue
• LRU Cache
• Implementation walkthrough — full service code
• Architecture reference — project tree, data flow, decisions

Next Steps

Start with elevenlabs-install-auth for setup, then apply this architecture. Use

elevenlabs-core-workflow-a and elevenlabs-core-workflow-b for feature implementation.