elevenlabs-reference-architecture

Implement ElevenLabs reference architecture for production TTS/voice applications. Use when designing new ElevenLabs integrations, reviewing project structure, or building a scalable audio generation service. Trigger: "elevenlabs architecture", "elevenlabs project structure", "how to organize elevenlabs", "TTS service architecture", "elevenlabs design patterns", "voice API architecture".

1,868 stars

Best use case

elevenlabs-reference-architecture is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Implement ElevenLabs reference architecture for production TTS/voice applications. Use when designing new ElevenLabs integrations, reviewing project structure, or building a scalable audio generation service. Trigger: "elevenlabs architecture", "elevenlabs project structure", "how to organize elevenlabs", "TTS service architecture", "elevenlabs design patterns", "voice API architecture".

Teams using elevenlabs-reference-architecture should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/elevenlabs-reference-architecture/SKILL.md --create-dirs "https://raw.githubusercontent.com/jeremylongshore/claude-code-plugins-plus-skills/main/plugins/saas-packs/elevenlabs-pack/skills/elevenlabs-reference-architecture/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/elevenlabs-reference-architecture/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How elevenlabs-reference-architecture Compares

Feature / Agentelevenlabs-reference-architectureStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Implement ElevenLabs reference architecture for production TTS/voice applications. Use when designing new ElevenLabs integrations, reviewing project structure, or building a scalable audio generation service. Trigger: "elevenlabs architecture", "elevenlabs project structure", "how to organize elevenlabs", "TTS service architecture", "elevenlabs design patterns", "voice API architecture".

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# ElevenLabs Reference Architecture

## Overview

Production-ready architecture for ElevenLabs TTS/voice applications. Covers project layout, service layers, caching, streaming, and multi-model orchestration.

## Prerequisites

- Understanding of layered architecture patterns
- ElevenLabs SDK knowledge (see `elevenlabs-sdk-patterns`)
- TypeScript project with async patterns
- Redis (optional, for distributed caching)

## Instructions

### Step 1: Project Structure

```
my-elevenlabs-service/
├── src/
│   ├── elevenlabs/
│   │   ├── client.ts            # Singleton client with retry config
│   │   ├── config.ts            # Environment-aware configuration
│   │   ├── models.ts            # Model selection logic
│   │   ├── errors.ts            # Error classification (see sdk-patterns)
│   │   └── types.ts             # TypeScript interfaces
│   ├── services/
│   │   ├── tts-service.ts       # Text-to-Speech orchestration
│   │   ├── voice-service.ts     # Voice management (clone, list, settings)
│   │   ├── audio-service.ts     # SFX, isolation, transcription
│   │   └── cache-service.ts     # Audio caching layer
│   ├── api/
│   │   ├── routes/
│   │   │   ├── tts.ts           # POST /api/tts
│   │   │   ├── voices.ts        # GET/POST /api/voices
│   │   │   ├── webhooks.ts      # POST /webhooks/elevenlabs
│   │   │   └── health.ts        # GET /health
│   │   └── middleware/
│   │       ├── rate-limit.ts    # Request throttling
│   │       └── auth.ts          # Your app's auth (not ElevenLabs auth)
│   ├── queue/
│   │   ├── tts-queue.ts         # Async TTS job processing
│   │   └── workers.ts           # Queue workers
│   └── monitoring/
│       ├── metrics.ts           # Latency, error rate, quota tracking
│       └── alerts.ts            # Budget and health alerts
├── tests/
│   ├── unit/
│   │   ├── tts-service.test.ts
│   │   └── cache-service.test.ts
│   └── integration/
│       └── tts-smoke.test.ts
├── config/
│   ├── development.json
│   ├── staging.json
│   └── production.json
└── .env.example
```

### Step 2: Configuration Layer

```typescript
// src/elevenlabs/config.ts
export interface ElevenLabsConfig {
  apiKey: string;
  environment: "development" | "staging" | "production";
  defaults: {
    modelId: string;
    voiceId: string;
    outputFormat: string;
    voiceSettings: {
      stability: number;
      similarity_boost: number;
      style: number;
      speed: number;
    };
  };
  performance: {
    maxConcurrency: number;
    timeoutMs: number;
    maxRetries: number;
  };
  cache: {
    enabled: boolean;
    maxSizeMB: number;
    ttlSeconds: number;
  };
}

const ENV_CONFIGS: Record<string, Partial<ElevenLabsConfig>> = {
  development: {
    defaults: {
      modelId: "eleven_flash_v2_5",    // Cheap + fast for dev
      voiceId: "21m00Tcm4TlvDq8ikWAM", // Rachel
      outputFormat: "mp3_22050_32",     // Small files
      voiceSettings: { stability: 0.5, similarity_boost: 0.75, style: 0, speed: 1 },
    },
    performance: { maxConcurrency: 2, timeoutMs: 30_000, maxRetries: 1 },
    cache: { enabled: true, maxSizeMB: 50, ttlSeconds: 3600 },
  },
  production: {
    defaults: {
      modelId: "eleven_multilingual_v2", // High quality for prod
      voiceId: "21m00Tcm4TlvDq8ikWAM",
      outputFormat: "mp3_44100_128",     // High quality
      voiceSettings: { stability: 0.5, similarity_boost: 0.75, style: 0, speed: 1 },
    },
    performance: { maxConcurrency: 10, timeoutMs: 60_000, maxRetries: 3 },
    cache: { enabled: true, maxSizeMB: 500, ttlSeconds: 86_400 },
  },
};

export function loadConfig(): ElevenLabsConfig {
  const env = process.env.NODE_ENV || "development";
  const envConfig = ENV_CONFIGS[env] || ENV_CONFIGS.development;

  return {
    apiKey: process.env.ELEVENLABS_API_KEY!,
    environment: env as any,
    ...envConfig,
  } as ElevenLabsConfig;
}
```

### Step 3: TTS Service Layer

```typescript
// src/services/tts-service.ts
import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js";
import PQueue from "p-queue";
import { loadConfig } from "../elevenlabs/config";
import { classifyError } from "../elevenlabs/errors";

export class TTSService {
  private client: ElevenLabsClient;
  private queue: PQueue;
  private config: ReturnType<typeof loadConfig>;

  constructor() {
    this.config = loadConfig();
    this.client = new ElevenLabsClient({
      apiKey: this.config.apiKey,
      maxRetries: this.config.performance.maxRetries,
      timeoutInSeconds: this.config.performance.timeoutMs / 1000,
    });
    this.queue = new PQueue({
      concurrency: this.config.performance.maxConcurrency,
    });
  }

  async generate(text: string, options?: {
    voiceId?: string;
    modelId?: string;
    outputFormat?: string;
    streaming?: boolean;
  }): Promise<ReadableStream | Buffer> {
    const voiceId = options?.voiceId || this.config.defaults.voiceId;
    const modelId = options?.modelId || this.config.defaults.modelId;
    const format = options?.outputFormat || this.config.defaults.outputFormat;

    return this.queue.add(async () => {
      const start = performance.now();

      try {
        if (options?.streaming) {
          return await this.client.textToSpeech.stream(voiceId, {
            text,
            model_id: modelId,
            output_format: format,
            voice_settings: this.config.defaults.voiceSettings,
          });
        }

        const audio = await this.client.textToSpeech.convert(voiceId, {
          text,
          model_id: modelId,
          output_format: format,
          voice_settings: this.config.defaults.voiceSettings,
        });

        const latency = performance.now() - start;
        console.log(`[TTS] ${text.length} chars, ${modelId}, ${latency.toFixed(0)}ms`);
        return audio;
      } catch (error) {
        throw classifyError(error);
      }
    }) as Promise<ReadableStream | Buffer>;
  }

  // Split long text into chunks with prosody context
  async generateLongText(text: string, voiceId?: string): Promise<Buffer[]> {
    const chunks = this.splitText(text, 4500); // Stay under 5000 limit
    const results: Buffer[] = [];

    for (let i = 0; i < chunks.length; i++) {
      const audio = await this.generate(chunks[i], {
        voiceId,
        // Pass context for natural prosody across chunks
      });
      results.push(audio as Buffer);
    }

    return results;
  }

  private splitText(text: string, maxChars: number): string[] {
    const chunks: string[] = [];
    const sentences = text.match(/[^.!?]+[.!?]+/g) || [text];
    let current = "";

    for (const sentence of sentences) {
      if ((current + sentence).length > maxChars) {
        if (current) chunks.push(current.trim());
        current = sentence;
      } else {
        current += sentence;
      }
    }
    if (current) chunks.push(current.trim());
    return chunks;
  }
}
```

### Step 4: Voice Management Service

```typescript
// src/services/voice-service.ts
export class VoiceService {
  private client: ElevenLabsClient;

  constructor(client: ElevenLabsClient) {
    this.client = client;
  }

  async listVoices(filter?: { category?: "premade" | "cloned" | "generated" }) {
    const { voices } = await this.client.voices.getAll();
    if (filter?.category) {
      return voices.filter(v => v.category === filter.category);
    }
    return voices;
  }

  async cloneVoice(name: string, description: string, audioFiles: NodeJS.ReadableStream[]) {
    return this.client.voices.add({
      name,
      description,
      files: audioFiles,
    });
  }

  async getVoiceSettings(voiceId: string) {
    return this.client.voices.getSettings(voiceId);
  }

  async updateVoiceSettings(voiceId: string, settings: {
    stability: number;
    similarity_boost: number;
  }) {
    return this.client.voices.editSettings(voiceId, settings);
  }

  async deleteVoice(voiceId: string) {
    return this.client.voices.delete(voiceId);
  }
}
```

### Step 5: Data Flow Diagram

```
                         ┌──────────────┐
                         │   Client     │
                         │  (Browser/   │
                         │   Mobile)    │
                         └──────┬───────┘
                                │
                         ┌──────▼───────┐
                         │   API Layer  │
                         │   /api/tts   │
                         │   /api/voice │
                         └──────┬───────┘
                                │
                    ┌───────────┼───────────┐
                    │           │           │
             ┌──────▼──┐ ┌─────▼─────┐ ┌──▼──────┐
             │  Cache   │ │   TTS     │ │  Voice  │
             │ Service  │ │  Service  │ │ Service │
             └──────┬───┘ └─────┬─────┘ └────────┘
                    │           │
              ┌─────▼─┐  ┌─────▼──────────┐
              │ Redis/ │  │ Concurrency    │
              │ LRU    │  │ Queue (p-queue)│
              └────────┘  └─────┬──────────┘
                                │
                         ┌──────▼───────┐
                         │  ElevenLabs  │
                         │  Client SDK  │
                         │  (singleton) │
                         └──────┬───────┘
                                │
                    ┌───────────┼───────────┐
                    │           │           │
             ┌──────▼──┐ ┌─────▼─────┐ ┌──▼──────┐
             │ /v1/tts  │ │ /v1/voices│ │ /v1/sfx │
             │ REST/WS  │ │  REST     │ │  REST   │
             └──────────┘ └───────────┘ └─────────┘
                    ElevenLabs API (api.elevenlabs.io)
```

### Step 6: Health Check Composition

```typescript
// src/api/routes/health.ts
export async function healthCheck() {
  const checks = await Promise.allSettled([
    checkElevenLabsConnectivity(),
    checkQuotaStatus(),
    checkCacheHealth(),
  ]);

  const elevenlabs = checks[0].status === "fulfilled" ? checks[0].value : null;
  const quota = checks[1].status === "fulfilled" ? checks[1].value : null;
  const cache = checks[2].status === "fulfilled" ? checks[2].value : null;

  const degraded = !elevenlabs || (quota && quota.pctUsed > 90);

  return {
    status: !elevenlabs ? "unhealthy" : degraded ? "degraded" : "healthy",
    services: { elevenlabs, quota, cache },
    timestamp: new Date().toISOString(),
  };
}
```

## Architecture Decisions

| Decision | Choice | Rationale |
|----------|--------|-----------|
| Client pattern | Singleton | One connection pool, shared retry config |
| Concurrency | p-queue | Respects plan limits, prevents 429 |
| Caching | LRU (local) or Redis (distributed) | Repeated content is common in TTS |
| Long text | Sentence-boundary splitting | Preserves natural speech prosody |
| Error handling | Classification + retry | Different strategies for 429 vs 401 vs 500 |
| Model selection | Environment-based | Flash in dev (cheap), Multilingual in prod (quality) |
| Streaming | HTTP streaming + WebSocket | HTTP for simple, WS for LLM integration |

## Error Handling

| Issue | Cause | Solution |
|-------|-------|----------|
| Circular dependencies | Wrong layering | Services depend on client, never reverse |
| Cold start latency | Client initialization | Pre-warm in server startup |
| Memory pressure | Unbounded audio cache | Set `maxSizeMB` on cache |
| Type errors | SDK version mismatch | Pin SDK version in package.json |

## Resources

- [ElevenLabs API Reference](https://elevenlabs.io/docs/api-reference/introduction)
- [ElevenLabs SDK Source](https://github.com/elevenlabs/elevenlabs-js)
- [p-queue](https://github.com/sindresorhus/p-queue)
- [LRU Cache](https://github.com/isaacs/node-lru-cache)

## 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.

Related Skills

workhuman-reference-architecture

1868
from jeremylongshore/claude-code-plugins-plus-skills

Workhuman reference architecture for employee recognition and rewards API. Use when integrating Workhuman Social Recognition, or building recognition workflows with HRIS systems. Trigger: "workhuman reference architecture".

wispr-reference-architecture

1868
from jeremylongshore/claude-code-plugins-plus-skills

Wispr Flow reference architecture for voice-to-text API integration. Use when integrating Wispr Flow dictation, WebSocket streaming, or building voice-powered applications. Trigger: "wispr reference architecture".

windsurf-reference-architecture

1868
from jeremylongshore/claude-code-plugins-plus-skills

Implement Windsurf reference architecture with optimal project structure and AI configuration. Use when designing workspace configuration for Windsurf, setting up team standards, or establishing architecture patterns that maximize Cascade effectiveness. Trigger with phrases like "windsurf architecture", "windsurf project structure", "windsurf best practices", "windsurf team setup", "optimize for cascade".

windsurf-architecture-variants

1868
from jeremylongshore/claude-code-plugins-plus-skills

Choose workspace architectures for different project scales in Windsurf. Use when deciding how to structure Windsurf workspaces for monorepos, multi-service setups, or polyglot codebases. Trigger with phrases like "windsurf workspace strategy", "windsurf monorepo", "windsurf project layout", "windsurf multi-service", "windsurf workspace size".

webflow-reference-architecture

1868
from jeremylongshore/claude-code-plugins-plus-skills

Implement Webflow reference architecture — layered project structure, client wrapper, CMS sync service, webhook handlers, and caching layer for production integrations. Trigger with phrases like "webflow architecture", "webflow project structure", "how to organize webflow", "webflow integration design", "webflow best practices".

vercel-reference-architecture

1868
from jeremylongshore/claude-code-plugins-plus-skills

Implement a Vercel reference architecture with layered project structure and best practices. Use when designing new Vercel projects, reviewing project structure, or establishing architecture standards for Vercel applications. Trigger with phrases like "vercel architecture", "vercel project structure", "vercel best practices layout", "how to organize vercel project".

vercel-architecture-variants

1868
from jeremylongshore/claude-code-plugins-plus-skills

Choose and implement Vercel architecture blueprints for different scales and use cases. Use when designing new Vercel projects, choosing between static, serverless, and edge architectures, or planning how to structure a multi-project Vercel deployment. Trigger with phrases like "vercel architecture", "vercel blueprint", "how to structure vercel", "vercel monorepo", "vercel multi-project".

veeva-reference-architecture

1868
from jeremylongshore/claude-code-plugins-plus-skills

Veeva Vault reference architecture for REST API and clinical operations. Use when working with Veeva Vault document management and CRM. Trigger: "veeva reference architecture".

vastai-reference-architecture

1868
from jeremylongshore/claude-code-plugins-plus-skills

Implement Vast.ai reference architecture for GPU compute workflows. Use when designing ML training pipelines, structuring GPU orchestration, or establishing architecture patterns for Vast.ai applications. Trigger with phrases like "vastai architecture", "vastai design pattern", "vastai project structure", "vastai ml pipeline".

twinmind-reference-architecture

1868
from jeremylongshore/claude-code-plugins-plus-skills

Production architecture for meeting AI systems using TwinMind: transcription pipeline, memory vault, action item workflow, and calendar integration. Use when implementing reference architecture, or managing TwinMind meeting AI operations. Trigger with phrases like "twinmind reference architecture", "twinmind reference architecture".

together-reference-architecture

1868
from jeremylongshore/claude-code-plugins-plus-skills

Together AI reference architecture for inference, fine-tuning, and model deployment. Use when working with Together AI's OpenAI-compatible API. Trigger: "together reference architecture".

techsmith-reference-architecture

1868
from jeremylongshore/claude-code-plugins-plus-skills

TechSmith reference architecture for Snagit COM API and Camtasia automation. Use when working with TechSmith screen capture and video editing automation. Trigger: "techsmith reference architecture".