Elevenlabs

ElevenLabs — AI Voice Synthesis & Cloning

Overview

You are an expert in ElevenLabs, the AI voice platform for high-quality text-to-speech, voice cloning, and conversational AI. You help developers build voice-enabled applications with natural-sounding speech, custom voice creation, multilingual support, and real-time streaming TTS for voice agents, audiobooks, podcasts, and accessibility features.

Instructions

Text-to-Speech

# Basic TTS — generate audio from text
from elevenlabs import ElevenLabs

client = ElevenLabs(api_key=os.environ["ELEVENLABS_API_KEY"])

# Generate and save audio
audio = client.text_to_speech.convert(
    voice_id="pNInz6obpgDQGcFmaJgB",    # "Rachel" — warm, professional
    text="Welcome to Bright Smile Dental. How can I help you today?",
    model_id="eleven_turbo_v2_5",         # Optimized for low latency (~200ms)
    voice_settings={
        "stability": 0.6,                 # Lower = more expressive, higher = more consistent
        "similarity_boost": 0.8,           # How closely to match the original voice
        "style": 0.3,                      # Style exaggeration (0-1)
        "use_speaker_boost": True,         # Enhance clarity
    },
)

# Save to file
with open("greeting.mp3", "wb") as f:
    for chunk in audio:
        f.write(chunk)

# Streaming TTS — for real-time applications
audio_stream = client.text_to_speech.convert_as_stream(
    voice_id="pNInz6obpgDQGcFmaJgB",
    text="Let me check our available appointments for next Tuesday.",
    model_id="eleven_turbo_v2_5",
    output_format="pcm_24000",            # Raw PCM for WebRTC/LiveKit
)

for chunk in audio_stream:
    send_to_audio_output(chunk)            # Stream directly to speaker

Voice Cloning

# Instant voice clone — from a single audio sample
voice = client.voices.add(
    name="Dr. Smith",
    files=[open("dr_smith_sample.mp3", "rb")],
    description="Calm, authoritative male voice for medical context",
    labels={"use_case": "voice_agent", "language": "en"},
)
print(f"Cloned voice ID: {voice.voice_id}")

# Professional voice clone (higher quality, requires consent)
# Needs 30+ minutes of clean audio for best results

Conversational AI Agent

# ElevenLabs Conversational AI — fully managed voice agent
from elevenlabs import ConversationalAI

agent = ConversationalAI(
    api_key=os.environ["ELEVENLABS_API_KEY"],
    agent_id="your-agent-id",             # Created in ElevenLabs dashboard
)

# WebSocket connection for real-time conversation
async def handle_call(websocket):
    async for audio_chunk in websocket:
        # Send caller audio to ElevenLabs
        response = await agent.process_audio(audio_chunk)
        # Send AI response audio back to caller
        await websocket.send(response.audio)

JavaScript / React

// Browser-based TTS
import { ElevenLabsClient } from "elevenlabs";

const client = new ElevenLabsClient({ apiKey: process.env.ELEVENLABS_KEY });

// Stream audio in browser
const response = await client.textToSpeech.convertAsStream(voiceId, {
  text: "Hello! How can I assist you?",
  model_id: "eleven_turbo_v2_5",
  output_format: "mp3_44100_128",
});

// Play audio using Web Audio API
const audioContext = new AudioContext();
const reader = response.getReader();
// ... decode and play chunks

Available Models

Model	Latency	Quality	Best For
eleven_turbo_v2_5	~200ms	High	Voice agents, real-time apps
eleven_multilingual_v2	~400ms	Highest	Multilingual, audiobooks
eleven_english_v1	~300ms	Good	English-only, cost-sensitive

Installation

pip install elevenlabs                    # Python
npm install elevenlabs                    # Node.js

Examples

Example 1: User asks to set up elevenlabs

User: "Help me set up elevenlabs for my project"

The agent should:

1. Check system requirements and prerequisites
2. Install or configure elevenlabs
3. Set up initial project structure
4. Verify the setup works correctly

Example 2: User asks to build a feature with elevenlabs

User: "Create a dashboard using elevenlabs"

The agent should:

1. Scaffold the component or configuration
2. Connect to the appropriate data source
3. Implement the requested feature
4. Test and validate the output

Guidelines

1. Turbo model for voice agents — Use eleven_turbo_v2_5 for real-time conversations; 200ms latency feels instant
2. Streaming for real-time — Use convert_as_stream instead of convert for voice agents; first audio chunk arrives in ~200ms
3. Voice settings tuning — Lower stability (0.3-0.5) for expressive narration; higher (0.7-0.9) for consistent voice agents
4. PCM output for WebRTC — Use pcm_24000 or pcm_16000 output format when feeding into WebRTC/LiveKit; no decoding overhead
5. Voice library — Browse ElevenLabs' voice library (1000+ voices) before cloning; many professional voices are already available
6. Pronunciation dictionary — Upload custom pronunciation rules for medical terms, brand names, and technical jargon
7. Character count billing — ElevenLabs bills per character; cache common phrases and greetings to reduce costs
8. SSML-like control — Use <break time="0.5s"/> in text for natural pauses; helps with phone menu options