ai-provider-elevenlabs

ElevenLabs Patterns

Quick Guide: Use the official @elevenlabs/elevenlabs-js package to interact with the ElevenLabs API. Use client.textToSpeech.convert() for full audio generation or client.textToSpeech.stream() for low-latency streaming. Voice settings (stability, similarityBoost, style) control output character. Use eleven_v3 for best quality, eleven_flash_v2_5 for lowest latency, or eleven_multilingual_v2 for stable long-form content. The SDK returns ReadableStream<Uint8Array> -- pipe to files or HTTP responses. Use @elevenlabs/client for real-time conversational AI agents.

---

<critical_requirements>

CRITICAL: Before Using This Skill

All code must follow project conventions in CLAUDE.md (kebab-case, named exports, import ordering, import type, named constants)

(You MUST use @elevenlabs/elevenlabs-js for server-side TTS, voice management, and speech-to-speech -- use @elevenlabs/client only for conversational AI agents)

(You MUST never hardcode API keys -- always use environment variables via process.env.ELEVENLABS_API_KEY which the SDK reads automatically)

(You MUST consume the ReadableStream<Uint8Array> returned by convert() and stream() -- unconsumed streams leak resources)

(You MUST choose the correct model for your use case -- eleven_v3 for quality, eleven_flash_v2_5 for speed, eleven_multilingual_v2 for long-form stability)

(You MUST pass voiceId as the first positional argument to all textToSpeech methods -- it is NOT inside the options object)

</critical_requirements>

---

Auto-detection: ElevenLabs, elevenlabs, ElevenLabsClient, textToSpeech.convert, textToSpeech.stream, eleven_multilingual_v2, eleven_flash_v2_5, eleven_v3, speechToSpeech, voices.search, voice cloning, ELEVENLABS_API_KEY, @elevenlabs/elevenlabs-js, @elevenlabs/client, text-to-speech, TTS, voice synthesis

When to use:

• Generating speech audio from text (narration, audiobooks, announcements)
• Streaming audio in real-time for low-latency playback
• Cloning voices from audio samples (instant or professional voice cloning)
• Converting speech from one voice to another (speech-to-speech)
• Building real-time conversational AI agents with voice interaction
• Controlling pronunciation with SSML or pronunciation dictionaries
• Generating audio with character-level timestamp alignment

Key patterns covered:

• Client initialization and configuration (retries, timeouts, API key)
• Text-to-speech conversion and streaming (convert, stream, timestamps)
• Voice settings (stability, similarityBoost, style, speed)
• Voice selection and management (voices.search, voices.get)
• Voice cloning (instant via voices.ivc.create)
• Speech-to-speech voice conversion
• WebSocket input streaming for real-time text-to-speech
• Pronunciation dictionaries and SSML
• Conversational AI agents (@elevenlabs/client)
• Model selection, output formats, error handling

When NOT to use:

• You need multi-provider voice AI (multiple TTS vendors) -- use a unified abstraction
• You only need browser-side audio playback without generation -- use the Web Audio API
• You need speech-to-text transcription only -- ElevenLabs has this, but it is a separate concern

---

Examples Index

• Core: Setup, TTS, Streaming & Voice Settings -- Client init, convert, stream, timestamps, voice settings, output formats
• Voices & Cloning -- Voice search, selection, instant voice cloning, speech-to-speech
• WebSocket & Conversational AI -- WebSocket input streaming, conversational AI agents, real-time patterns
• Quick API Reference -- Model IDs, method signatures, output formats, error types, voice settings

---

Philosophy

The ElevenLabs SDK provides direct access to the most advanced voice AI API available. It wraps the ElevenLabs REST API with full TypeScript types, streaming support, and automatic retries.

Core principles:

1. Streams everywhere -- All audio methods return ReadableStream<Uint8Array>. You pipe them to files, HTTP responses, or audio players. The SDK never buffers entire audio files in memory.
2. Voice settings are the primary control surface -- stability, similarityBoost, style, and speed shape every generation. Learn these four knobs well.
3. Model selection drives the quality/latency tradeoff -- eleven_v3 for best quality, eleven_flash_v2_5 for sub-75ms latency, eleven_multilingual_v2 for stable long-form.
4. Two packages for two use cases -- @elevenlabs/elevenlabs-js for server-side TTS/voice management, @elevenlabs/client for browser-side conversational AI agents.
5. Built-in resilience -- The SDK retries on 408, 409, 429, and 5xx errors (2 retries by default) with configurable timeouts.

---

Core Patterns

Pattern 1: Client Setup

Initialize the ElevenLabs client. It auto-reads ELEVENLABS_API_KEY from the environment.

// lib/elevenlabs.ts -- basic setup
import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js";

const client = new ElevenLabsClient();
export { client };

// lib/elevenlabs.ts -- production configuration
import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js";

const TIMEOUT_SECONDS = 60;
const MAX_RETRIES = 3;

const client = new ElevenLabsClient({
  apiKey: process.env.ELEVENLABS_API_KEY,
  timeoutInSeconds: TIMEOUT_SECONDS,
  maxRetries: MAX_RETRIES,
});

export { client };

Why good: Minimal setup, env var auto-detected, named constants for production settings

// BAD: Hardcoded API key
const client = new ElevenLabsClient({
  apiKey: "sk-1234567890abcdef",
});

Why bad: Hardcoded API key is a security breach risk, will leak in version control

See: examples/core.md for per-request overrides, error handling

---

Pattern 2: Text-to-Speech (Convert)

Generate complete audio from text. Returns ReadableStream<Uint8Array>.

import { createWriteStream } from "node:fs";
import { Readable } from "node:stream";

const VOICE_ID = "JBFqnCBsd6RMkjVDRZzb"; // George

const audio = await client.textToSpeech.convert(VOICE_ID, {
  text: "Welcome to the application.",
  modelId: "eleven_multilingual_v2",
  outputFormat: "mp3_44100_128",
});

// Pipe to file
const readable = Readable.fromWeb(audio);
const fileStream = createWriteStream("output.mp3");
readable.pipe(fileStream);

Why good: voiceId as first arg (required), model and format explicit, stream piped to file without buffering

// BAD: voiceId inside options object
const audio = await client.textToSpeech.convert({
  voiceId: VOICE_ID, // WRONG: voiceId is a positional argument
  text: "Hello",
});

Why bad: voiceId is the first positional argument, not an options field -- this will throw a type error

See: examples/core.md for timestamps, HTTP response piping

---

Pattern 3: Text-to-Speech (Stream)

Stream audio for real-time playback with lower latency than convert().

const VOICE_ID = "JBFqnCBsd6RMkjVDRZzb";
const LATENCY_OPTIMIZATION = 2;

const audioStream = await client.textToSpeech.stream(VOICE_ID, {
  text: "This streams with lower latency for real-time playback.",
  modelId: "eleven_flash_v2_5",
  optimizeStreamingLatency: LATENCY_OPTIMIZATION,
  outputFormat: "mp3_44100_128",
});

// Consume the stream
for await (const chunk of audioStream) {
  process.stdout.write(chunk); // Or pipe to audio player / HTTP response
}

Why good: Uses stream() for lower latency, eleven_flash_v2_5 for speed, optimizeStreamingLatency reduces first-byte time

// BAD: Stream created but never consumed
const audioStream = await client.textToSpeech.stream(VOICE_ID, {
  text: "This audio is lost",
  modelId: "eleven_flash_v2_5",
});
// Stream never consumed -- resources leaked

Why bad: Unconsumed streams leak resources and the audio data is silently lost

See: examples/core.md for streaming to HTTP responses

---

Pattern 4: Voice Settings

Control voice characteristics with voiceSettings.

const VOICE_ID = "JBFqnCBsd6RMkjVDRZzb";

const audio = await client.textToSpeech.convert(VOICE_ID, {
  text: "Emotional and expressive delivery.",
  modelId: "eleven_v3",
  voiceSettings: {
    stability: 0.3, // Lower = more expressive/variable
    similarityBoost: 0.8, // Higher = closer to original voice
    style: 0.5, // Higher = more style exaggeration
    useSpeakerBoost: true, // Enhanced speaker similarity (adds latency)
    speed: 1.0, // 0.7-1.3 range typical
  },
});

Why good: All settings explicit with clear purpose, stability lowered for expressive content

// BAD: Using extreme values without understanding
const audio = await client.textToSpeech.convert(VOICE_ID, {
  text: "Extreme settings cause artifacts.",
  modelId: "eleven_v3",
  voiceSettings: {
    stability: 0.0, // Too unstable -- garbled output
    similarityBoost: 1.0, // Combined with low stability = artifacts
    style: 1.0, // Maximum exaggeration -- unnatural
  },
});

Why bad: Extreme values produce artifacts; stability: 0.0 with high similarityBoost is unstable. Start with defaults and adjust incrementally.

See: reference.md for voice settings ranges and recommended starting values

---

Pattern 5: Voice Selection and Management

Find and select voices from the ElevenLabs voice library.

// Search all available voices
const { voices } = await client.voices.search();

for (const voice of voices) {
  console.log(`${voice.name} (${voice.voiceId}) - ${voice.category}`);
}

// Get a specific voice by ID
const VOICE_ID = "JBFqnCBsd6RMkjVDRZzb";
const voice = await client.voices.get(VOICE_ID);
console.log(voice.name, voice.settings);

Why good: Uses voices.search() to discover available voices, voices.get() for details

See: examples/voices.md for filtering, voice cloning, speech-to-speech

---

Pattern 6: Voice Cloning (Instant)

Create an instant voice clone from audio samples.

import { createReadStream } from "node:fs";

const voice = await client.voices.ivc.create({
  name: "My Custom Voice",
  files: [createReadStream("sample1.mp3"), createReadStream("sample2.mp3")],
  removeBackgroundNoise: true,
});

console.log(`Created voice: ${voice.voiceId}`);

// Use the cloned voice for TTS
const audio = await client.textToSpeech.convert(voice.voiceId, {
  text: "Speaking in the cloned voice.",
  modelId: "eleven_multilingual_v2",
});

Why good: removeBackgroundNoise improves quality, multiple samples improve accuracy, immediately usable

See: examples/voices.md for professional voice cloning, sample validation

---

Pattern 7: Speech-to-Speech

Convert speech from one voice to another while preserving emotion and cadence.

import { createReadStream } from "node:fs";

const TARGET_VOICE_ID = "JBFqnCBsd6RMkjVDRZzb";

const convertedAudio = await client.speechToSpeech.convert(TARGET_VOICE_ID, {
  audio: createReadStream("input-speech.mp3"),
  modelId: "eleven_multilingual_sts_v2",
  voiceSettings: {
    stability: 0.5,
    similarityBoost: 0.75,
  },
});

Why good: Uses STS-specific model, preserves source emotion, voice settings control output fidelity

See: examples/voices.md for streaming STS, English-only model

---

Pattern 8: Error Handling

Catch SDK errors and handle specific failure modes.

import {
  ElevenLabsError,
  ElevenLabsTimeoutError,
} from "@elevenlabs/elevenlabs-js";

const VOICE_ID = "JBFqnCBsd6RMkjVDRZzb";

try {
  const audio = await client.textToSpeech.convert(VOICE_ID, {
    text: "Hello, world.",
    modelId: "eleven_multilingual_v2",
  });
} catch (error) {
  if (error instanceof ElevenLabsTimeoutError) {
    console.error("Request timed out -- increase timeoutInSeconds or retry");
  } else if (error instanceof ElevenLabsError) {
    console.error(`ElevenLabs API error: ${error.message}`);
    console.error(`Status: ${error.statusCode}`);
    console.error(`Body: ${JSON.stringify(error.body)}`);
  } else {
    throw error; // Re-throw non-ElevenLabs errors
  }
}

Why good: Catches specific error types, logs status code and body for debugging, re-throws unknown errors

See: examples/core.md for stream error handling, retry patterns

---

Performance Optimization

Model Selection for Latency/Quality

Best quality + expressiveness  -> eleven_v3 (70+ languages)
Long-form stability            -> eleven_multilingual_v2 (29 languages, 10K char limit)
Lowest latency (<75ms)         -> eleven_flash_v2_5 (32 languages, 40K char limit)
English-only low latency       -> eleven_flash_v2 (English only, 30K char limit)
Voice design from text prompt  -> eleven_ttv_v3 (70+ languages)

Key Optimization Patterns

• Use stream() instead of convert() for user-facing audio -- playback starts before generation completes
• Set optimizeStreamingLatency (0-4) on stream() calls -- higher values reduce latency but may affect text normalization
• Use eleven_flash_v2_5 for real-time applications -- sub-75ms latency at 50% lower cost
• Use previous_request_ids for multi-part generation -- maintains voice consistency across segments
• Batch multiple short texts into single requests when possible -- reduces API call overhead
• Cache generated audio for static content -- avoid re-generating identical text
• Use outputFormat: "pcm_16000" for server-side processing pipelines -- lower bandwidth than MP3

---

<decision_framework>

Decision Framework

Which Model to Choose

What is your priority?
+-- Best quality / expressiveness -> eleven_v3
+-- Lowest latency (<75ms) -> eleven_flash_v2_5
+-- Long-form stability (audiobooks) -> eleven_multilingual_v2
+-- English-only speed -> eleven_flash_v2
+-- Voice design from text description -> eleven_ttv_v3
+-- Speech-to-speech conversion -> eleven_multilingual_sts_v2 (or eleven_english_sts_v2)

convert() vs stream()

Is the audio user-facing with real-time playback?
+-- YES -> Use stream() for progressive playback
|   +-- Need timestamps? -> streamWithTimestamps()
+-- NO -> Use convert() for complete audio
    +-- Need timestamps? -> convertWithTimestamps()
    +-- Saving to file? -> convert() and pipe to WriteStream

Which Package to Use

What are you building?
+-- Server-side TTS, voice management, STS -> @elevenlabs/elevenlabs-js
+-- Browser conversational AI agent -> @elevenlabs/client
+-- React conversational AI agent -> @elevenlabs/react
+-- WebSocket text input streaming -> @elevenlabs/elevenlabs-js (or raw WebSocket)

Output Format Selection

What is the audio destination?
+-- Web browser playback -> mp3_44100_128 (universal compatibility)
+-- Low-bandwidth streaming -> opus_48000_64 (smaller files)
+-- Audio processing pipeline -> pcm_16000 or pcm_44100 (raw audio)
+-- Telephony / IVR -> ulaw_8000 or alaw_8000 (legacy codecs)
+-- High-quality archival -> wav_44100 or mp3_44100_192

</decision_framework>

---

<red_flags>

RED FLAGS

High Priority Issues:

• Hardcoding API keys instead of using process.env.ELEVENLABS_API_KEY (security breach risk)
• Not consuming streams returned by convert() or stream() (resources leaked, audio lost)
• Passing voiceId inside the options object instead of as the first positional argument (type error)
• Using deprecated eleven_turbo_v2_5 instead of eleven_flash_v2_5 (migrate to Flash models)
• Using deprecated eleven_monolingual_v1 or eleven_multilingual_v1 (use v2+ models)

Medium Priority Issues:

• Not setting timeoutInSeconds for production (default is 240 seconds -- may be too long or too short)
• Using stability: 0.0 or extreme voice settings without testing (produces artifacts)
• Not using optimizeStreamingLatency when streaming to users (adds unnecessary latency)
• Ignoring outputFormat and relying on the default when a specific format is needed
• Creating voice clones with a single short sample (multiple 30s+ samples improve quality)

Common Mistakes:

• Confusing @elevenlabs/elevenlabs-js (server-side TTS SDK) with @elevenlabs/client (conversational AI agents SDK) -- they serve different purposes
• Using textToSpeech.convert() for real-time playback instead of textToSpeech.stream() -- convert waits for full generation
• Sending text longer than the model's character limit (10K for multilingual_v2, 40K for flash_v2_5, 5K for v3) -- request will fail
• Not using previous_request_ids for multi-part audio -- causes voice inconsistency between segments
• Using eleven_v3 when latency matters -- it has higher latency than Flash models

Gotchas & Edge Cases:

• The SDK auto-retries on 408, 409, 429, and 5xx errors -- 2 retries by default. Set maxRetries: 0 if you handle retries yourself.
• convert() and stream() both return ReadableStream<Uint8Array> but stream() starts sending data before generation completes (lower time-to-first-byte).
• convertWithTimestamps() returns { audioBase64, alignment } NOT a stream -- the entire audio is base64-encoded.
• streamWithTimestamps() returns an SSE Stream<ChunkWithTimestamps> -- each chunk has audio data AND character timing.
• Voice settings are optional -- if omitted, the voice's default settings are used. Override per-request for fine-tuning.
• The play() helper function from the SDK requires MPV and FFmpeg installed locally -- not suitable for production servers.
• WebSocket input streaming text must end with a space character for proper buffering.
• WebSocket chunk_length_schedule defaults to [120, 160, 250, 290] characters -- audio generation starts after the first threshold.
• Pronunciation dictionaries are limited to 3 per request and must be provided in the first WebSocket message.
• enable_ssml_parsing must be set as a query parameter on the WebSocket connection, not in the text message.
• The speed voice setting accepts values roughly in the 0.7-1.3 range for natural-sounding output.
• Free tier has 2-4 concurrent request limits -- higher tiers get elevated concurrency.

</red_flags>

---

<critical_reminders>

CRITICAL REMINDERS

All code must follow project conventions in CLAUDE.md (kebab-case, named exports, import ordering, import type, named constants)

(You MUST use @elevenlabs/elevenlabs-js for server-side TTS, voice management, and speech-to-speech -- use @elevenlabs/client only for conversational AI agents)

(You MUST never hardcode API keys -- always use environment variables via process.env.ELEVENLABS_API_KEY which the SDK reads automatically)

(You MUST consume the ReadableStream<Uint8Array> returned by convert() and stream() -- unconsumed streams leak resources)

(You MUST choose the correct model for your use case -- eleven_v3 for quality, eleven_flash_v2_5 for speed, eleven_multilingual_v2 for long-form stability)

(You MUST pass voiceId as the first positional argument to all textToSpeech methods -- it is NOT inside the options object)

Failure to follow these rules will produce broken, insecure, or degraded voice AI integrations.

</critical_reminders>