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elevenlabs-agents Build conversational AI voice agents with ElevenLabs Platform using React, JavaScript, React Native, or Swift SDKs.
Configure agents, tools (client/server/MCP), RAG knowledge bases, multi-voice, and Scribe real-time STT.
Use when: building voice chat interfaces, implementing AI phone agents with Twilio, configuring agent workflows
or tools, adding RAG knowledge bases, testing with CLI "agents as code", or troubleshooting deprecated @11labs
packages, Android audio cutoff, CSP violations, dynamic variables, or WebRTC config.
Keywords: ElevenLabs Agents, ElevenLabs voice agents, AI voice agents, conversational AI, @elevenlabs/react, @elevenlabs/client, @elevenlabs/react-native, @elevenlabs/elevenlabs-js, @elevenlabs/agents-cli, elevenlabs SDK, voice AI, TTS, text-to-speech, ASR, speech recognition, turn-taking model, WebRTC voice, WebSocket voice, ElevenLabs conversation, agent system prompt, agent tools, agent knowledge base, RAG voice agents, multi-voice agents, pronunciation dictionary, voice speed control,
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直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
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Zipをダウンロード ダウンロード中... Build backend AI with Vercel AI SDK v5/v6. Covers v6 beta (Agent abstraction, tool approval, reranking),
v4→v5 migration (breaking changes), latest models (GPT-5/5.1, Claude 4.x, Gemini 2.5), Workers startup
fix, and 12 error solutions (AI_APICallError, AI_NoObjectGeneratedError, streamText silent errors).
Use when: implementing AI SDK v5/v6, migrating v4→v5, troubleshooting errors, fixing Workers startup
issues, or updating to latest models.
Build React chat interfaces with Vercel AI SDK v5/v6. Covers v6 beta (agent integration, tool approval,
auto-submit), v4→v5 migration (breaking changes), useChat/useCompletion/useObject/useAssistant hooks,
and 12 UI error solutions (stream parsing, stale body values, React update depth).
Use when: implementing AI SDK v5/v6 chat UIs, migrating v4→v5, troubleshooting "useChat failed to parse
stream", "useChat no response", or "stale body values" errors, or integrating OpenAI assistants.
name elevenlabs-agents description Build conversational AI voice agents with ElevenLabs Platform using React, JavaScript, React Native, or Swift SDKs.
Configure agents, tools (client/server/MCP), RAG knowledge bases, multi-voice, and Scribe real-time STT.
Use when: building voice chat interfaces, implementing AI phone agents with Twilio, configuring agent workflows
or tools, adding RAG knowledge bases, testing with CLI "agents as code", or troubleshooting deprecated @11labs
packages, Android audio cutoff, CSP violations, dynamic variables, or WebRTC config.
Keywords: ElevenLabs Agents, ElevenLabs voice agents, AI voice agents, conversational AI, @elevenlabs/react, @elevenlabs/client, @elevenlabs/react-native, @elevenlabs/elevenlabs-js, @elevenlabs/agents-cli, elevenlabs SDK, voice AI, TTS, text-to-speech, ASR, speech recognition, turn-taking model, WebRTC voice, WebSocket voice, ElevenLabs conversation, agent system prompt, agent tools, agent knowledge base, RAG voice agents, multi-voice agents, pronunciation dictionary, voice speed control, elevenlabs scribe, @11labs deprecated, Android audio cutoff, CSP violation elevenlabs, dynamic variables elevenlabs, case-sensitive tool names, webhook authentication
license MIT metadata {"version":"1.1.0","last_updated":"2025-11-03T00:00:00.000Z","production_tested":true,"packages":[{"name":"@elevenlabs/elevenlabs-js","version":"2.21.0"},{"name":"@elevenlabs/agents-cli","version":"0.2.0"},{"name":"@elevenlabs/react","version":"0.9.1"},{"name":"@elevenlabs/client","version":"0.9.1"},{"name":"@elevenlabs/react-native","version":"0.5.2"}],"documentation":["https://elevenlabs.io/docs/agents-platform/overview","https://elevenlabs.io/docs/api-reference","https://github.com/elevenlabs/elevenlabs-examples"],"errors_prevented":"17+","token_savings":"~73%"}
ElevenLabs Agents Platform
Overview
ElevenLabs Agents Platform is a comprehensive solution for building production-ready conversational AI voice agents. The platform coordinates four core components:
ASR (Automatic Speech Recognition) - Converts speech to text (32+ languages, sub-second latency)LLM (Large Language Model) - Reasoning and response generation (GPT, Claude, Gemini, custom models)TTS (Text-to-Speech) - Converts text to speech (5000+ voices, 31 languages, low latency)Turn-Taking Model - Proprietary model that handles conversation timing and interruptions
🚨 Package Updates (November 2025)
ElevenLabs migrated to new scoped packages in August 2025:
DEPRECATED (Do not use):
@11labs/react → DEPRECATED @11labs/client → DEPRECATED
Current packages:
npm install @elevenlabs/react@0.9.1 # React SDK
npm install @elevenlabs/client@0.9.1 # JavaScript SDK
npm install @elevenlabs/react-native@0.5.2 # React Native SDK
npm install @elevenlabs/elevenlabs-js@2.21.0 # Base SDK
npm install -g @elevenlabs/agents-cli@0.2.0 # CLI
If you have old packages installed, uninstall them first:
npm uninstall @11labs/react @11labs/client
When to Use This Skill
Use this skill when:
Building voice-enabled customer support agents
Creating interactive voice response (IVR) systems
Developing conversational AI applications
Integrating telephony (Twilio, SIP trunking)
Implementing voice chat in web/mobile apps
Configuring agents via CLI ("agents as code")
Setting up RAG/knowledge bases for agents
Integrating MCP (Model Context Protocol) servers
Building HIPAA/GDPR-compliant voice systems
Optimizing LLM costs with caching strategies
Platform Capabilities
Design & Configure :
Multi-step workflows with visual builder
System prompt engineering (6-component framework)
5000+ voices across 31 languages
Pronunciation dictionaries (IPA/CMU formats)
Speed control (0.7x-1.2x)
RAG-powered knowledge bases
Dynamic variables and personalization
React SDK (@elevenlabs/react)
JavaScript SDK (@elevenlabs/client)
React Native SDK (@elevenlabs/react-native)
Swift SDK (iOS/macOS)
Embeddable widget
Telephony integration (Twilio, SIP)
Scribe (Real-Time Speech-to-Text) - Beta
Automated testing (scenario, tool call, load)
Conversation analysis and evaluation
Analytics dashboard (resolution rates, sentiment, compliance)
Privacy controls (GDPR, HIPAA, SOC 2)
Cost optimization (LLM caching, model swapping, burst pricing)
CLI for "agents as code" workflow
1. Quick Start (3 Integration Paths)
Path A: React SDK (Embedded Voice Chat) For building voice chat interfaces in React applications.
npm install @elevenlabs/react zod
import { useConversation } from '@elevenlabs/react';
import { z } from 'zod';
export default function VoiceChat() {
const { startConversation, stopConversation, status } = useConversation({
// Public agent (no API key needed)
agentId: 'your-agent-id',
// OR private agent (requires API key)
apiKey: process.env.NEXT_PUBLIC_ELEVENLABS_API_KEY,
// OR signed URL (server-generated, most secure)
signedUrl: '/api/elevenlabs/auth',
// Client-side tools (browser functions)
clientTools: {
updateCart: {
description: "Update the shopping cart",
parameters: z.object({
item: z.string(),
quantity: z.number()
}),
handler: async ({ item, quantity }) => {
console.log('Updating cart:', item, quantity);
return { success: true };
}
}
},
// Event handlers
onConnect: () => console.log('Connected'),
onDisconnect: () => console.log('Disconnected'),
onEvent: (event) => {
switch (event.type) {
case 'transcript':
console.log('User said:', event.data.text);
break;
case 'agent_response':
console.log('Agent replied:', event.data.text);
break;
}
},
// Regional compliance (GDPR, data residency)
serverLocation: 'us' // 'us' | 'global' | 'eu-residency' | 'in-residency'
});
return (
<div>
<button onClick={startConversation}>Start Conversation</button>
<button onClick={stopConversation}>Stop</button>
<p>Status: {status}</p>
</div>
);
}
Path B: CLI ("Agents as Code") For managing agents via code with version control and CI/CD.
npm install -g @elevenlabs/agents-cli
# or
pnpm install -g @elevenlabs/agents-cli
# 1. Authenticate
elevenlabs auth login
# 2. Initialize project (creates agents.json, tools.json, tests.json)
elevenlabs agents init
# 3. Create agent from template
elevenlabs agents add "Support Agent" --template customer-service
# 4. Configure in agent_configs/support-agent.json
# 5. Push to platform
elevenlabs agents push --env dev
# 6. Test
elevenlabs agents test "Support Agent"
# 7. Deploy to production
elevenlabs agents push --env prod
Project Structure Created :
your_project/
├── agents.json # Agent registry
├── tools.json # Tool configurations
├── tests.json # Test configurations
├── agent_configs/ # Individual agent files
├── tool_configs/ # Tool configuration files
└── test_configs/ # Test configuration files
Path C: API (Programmatic Agent Management) For creating agents dynamically (multi-tenant, SaaS platforms).
import { ElevenLabsClient } from 'elevenlabs';
const client = new ElevenLabsClient({
apiKey: process.env.ELEVENLABS_API_KEY
});
// Create agent
const agent = await client.agents.create({
name: 'Support Bot',
conversation_config: {
agent: {
prompt: {
prompt: "You are a helpful customer support agent.",
llm: "gpt-4o",
temperature: 0.7
},
first_message: "Hello! How can I help you today?",
language: "en"
},
tts: {
model_id: "eleven_turbo_v2_5",
voice_id: "your-voice-id"
}
}
});
console.log('Agent created:', agent.agent_id);
2. Agent Configuration
System Prompt Architecture (6 Components) ElevenLabs recommends structuring agent prompts using 6 components:
1. Personality Define the agent's identity, role, and character traits.
You are Alex, a friendly and knowledgeable customer support specialist at TechCorp.
You have 5 years of experience helping customers solve technical issues.
You're patient, empathetic, and always maintain a positive attitude.
2. Environment Describe the communication context (phone, web chat, video call).
You're speaking with customers over the phone. Communication is voice-only.
Customers may have background noise or poor connection quality.
Speak clearly and occasionally use thoughtful pauses for emphasis.
3. Tone Specify formality, speech patterns, humor, and verbosity.
Tone: Professional yet warm. Use contractions ("I'm" instead of "I am") to sound natural.
Avoid jargon unless the customer uses it first. Keep responses concise (2-3 sentences max).
Use encouraging phrases like "I'll be happy to help with that" and "Let's get this sorted for you."
4. Goal Define objectives and success criteria.
Primary Goal: Resolve customer technical issues on the first call.
Secondary Goals:
- Verify customer identity securely
- Document issue details accurately
- Offer proactive solutions
- End calls with confirmation that the issue is resolved
Success Criteria: Customer verbally confirms their issue is resolved.
5. Guardrails Set boundaries, prohibited topics, and ethical constraints.
Guardrails:
- Never provide medical, legal, or financial advice
- Do not share confidential company information
- If asked about competitors, politely redirect to TechCorp's offerings
- Escalate to a human supervisor if customer becomes abusive
- Never make promises about refunds or credits without verification
6. Tools Describe available external capabilities and when to use them.
Available Tools:
1. lookup_order(order_id) - Fetch order details from database. Use when customer mentions an order number.
2. transfer_to_supervisor() - Escalate to human agent. Use when issue requires manager approval.
3. send_password_reset(email) - Trigger password reset email. Use when customer can't access account.
Always explain to the customer what you're doing before calling a tool.
{
"agent": {
"prompt": {
"prompt": "Personality:\nYou are Alex, a friendly customer support specialist.\n\nEnvironment:\nYou're speaking with customers over the phone.\n\nTone:\nProfessional yet warm. Keep responses concise.\n\nGoal:\nResolve technical issues on the first call.\n\nGuardrails:\n- Never provide medical/legal/financial advice\n- Escalate abusive customers\n\nTools:\n- lookup_order(order_id) - Fetch order details\n- transfer_to_supervisor() - Escalate to human",
"llm": "gpt-4o",
"temperature": 0.7,
"max_tokens": 500
}
}
}
Turn-Taking Modes Controls when the agent interrupts or waits for the user to finish speaking.
Mode Behavior Best For Eager Responds quickly, jumps in at earliest opportunity Fast-paced support, quick orders Normal Balanced, waits for natural conversation breaks General customer service (default) Patient Waits longer, allows detailed user responses Information collection, therapy, tutoring
{
"conversation_config": {
"turn": {
"mode": "patient" // "eager" | "normal" | "patient"
}
}
}
Eager : Fast food ordering, quick FAQs, urgent notificationsNormal : General support, product inquiries, appointment bookingPatient : Detailed form filling, emotional support, educational tutoring
Eager mode can feel interruptive to some users
Patient mode may feel slow in fast-paced contexts
Can be dynamically adjusted in workflows for context-aware behavior
Workflows (Visual Builder) Create branching conversation flows with subagent nodes and conditional routing.
Subagent Nodes - Override base agent config (change prompt, voice, turn-taking)Tool Nodes - Guarantee tool execution (unlike tools in subagents) {
"workflow": {
"nodes": [
{
"id": "node_1",
"type": "subagent",
"config": {
"system_prompt": "You are now a technical support specialist. Ask detailed diagnostic questions.",
"turn_eagerness": "patient",
"voice_id": "tech_support_voice_id"
}
},
{
"id": "node_2",
"type": "tool",
"tool_name": "transfer_to_human"
}
],
"edges": [
{
"from": "node_1",
"to": "node_2",
"condition": "user_requests_escalation"
}
]
}
}
Multi-department routing (sales → support → billing)
Decision trees ("press 1 for sales, 2 for support")
Role-playing scenarios (customer vs agent voices)
Escalation paths (bot → human transfer)
Workflows add ~100-200ms latency per node transition
Tool nodes guarantee execution (subagents may skip tools)
Edges can create infinite loops if not tested properly
Dynamic Variables & Personalization Inject runtime data into prompts, first messages, and tool parameters using {{var_name}} syntax.
System Variables (Auto-Available) :
{{system__agent_id}} // Current agent ID
{{system__conversation_id}} // Conversation ID
{{system__caller_id}} // Phone number (telephony only)
{{system__called_number}} // Called number (telephony only)
{{system__call_duration_secs}} // Call duration
{{system__time_utc}} // Current UTC time
{{system__call_sid}} // Twilio call SID (Twilio only)
// Provide when starting conversation
const conversation = await client.conversations.create({
agent_id: "agent_123",
dynamic_variables: {
user_name: "John",
account_tier: "premium",
order_id: "ORD-12345"
}
});
Secret Variables (For API Keys):
{{secret__stripe_api_key}}
{{secret__database_password}}
Important : Secret variables only used in headers, never sent to LLM providers.
{
"agent": {
"prompt": {
"prompt": "You are helping {{user_name}}, a {{account_tier}} customer."
},
"first_message": "Hello {{user_name}}! I see you're calling about order {{order_id}}."
}
}
Gotcha : Missing variables cause "Missing required dynamic variables" error. Always provide all referenced variables when starting conversation.
Authentication Patterns Option 1: Public Agents (No API Key)
const { startConversation } = useConversation({
agentId: 'your-public-agent-id' // Anyone can use
});
Option 2: Private Agents with API Key
const { startConversation } = useConversation({
agentId: 'your-private-agent-id',
apiKey: process.env.NEXT_PUBLIC_ELEVENLABS_API_KEY
});
⚠️ Warning : Never expose API keys in client-side code. Use signed URLs instead.
Option 3: Signed URLs (Recommended for Production)
// Server-side (Next.js API route)
import { ElevenLabsClient } from 'elevenlabs';
export async function POST(req: Request) {
const client = new ElevenLabsClient({
apiKey: process.env.ELEVENLABS_API_KEY // Server-side only
});
const signedUrl = await client.convai.getSignedUrl({
agent_id: 'your-agent-id'
});
return Response.json({ signedUrl });
}
// Client-side
const { startConversation } = useConversation({
agentId: 'your-agent-id',
signedUrl: await fetch('/api/elevenlabs/auth').then(r => r.json()).then(d => d.signedUrl)
});
3. Voice & Language Features
Multi-Voice Support Dynamically switch between different voices during a single conversation.
Multi-character storytelling (different voice per character)
Language tutoring (native speaker voices for each language)
Role-playing scenarios (customer vs agent)
Emotional agents (different voices for different moods)
{
"agent": {
"prompt": {
"prompt": "When speaking as the customer, use voice_id 'customer_voice_abc123'. When speaking as the agent, use voice_id 'agent_voice_def456'."
}
}
}
Voice switching adds ~200ms latency per switch
Requires careful prompt engineering to trigger switches correctly
Not all voices work equally well for all characters
Pronunciation Dictionary Customize how the agent pronounces specific words or phrases.
IPA (International Phonetic Alphabet)CMU (Carnegie Mellon University Pronouncing Dictionary)Word Substitutions (replace words before TTS) {
"pronunciation_dictionary": [
{
"word": "ElevenLabs",
"pronunciation": "ɪˈlɛvənlæbz",
"format": "ipa"
},
{
"word": "API",
"pronunciation": "ey-pee-ay",
"format": "cmu"
},
{
"word": "AI",
"substitution": "artificial intelligence"
}
]
}
Brand names (e.g., "IKEA" → "ee-KAY-uh")
Acronyms (e.g., "API" → "A-P-I" or "ay-pee-eye")
Technical terms
Character names in storytelling
Gotcha : Only Turbo v2/v2.5 models support phoneme-based pronunciation. Other models silently skip phoneme entries but still process word substitutions.
Speed Control Adjust speaking speed dynamically (0.7x - 1.2x).
{
"voice_settings": {
"speed": 1.0 // 0.7 = slow, 1.0 = normal, 1.2 = fast
}
}
Slow (0.7x-0.9x) : Accessibility, children, non-native speakersNormal (1.0x) : Default for most use casesFast (1.1x-1.2x) : Urgent notifications, power users
Use 0.9x-1.1x for natural-sounding adjustments
Extreme values (below 0.7 or above 1.2) degrade quality
Speed can be adjusted per agent, not per utterance
Voice Design Create custom voices using ElevenLabs Voice Design tool.
Navigate to Voice Library → Create Voice
Use Voice Design (text-to-voice) or Voice Cloning (sample audio)
Test voice with sample text
Save voice to library
Use voice_id in agent configuration
Voice Cloning Best Practices :
Use clean audio samples (no background noise, music, or pops)
Maintain consistent microphone distance
Avoid extreme volumes (whispering or shouting)
1-2 minutes of audio recommended
Gotcha : Using English-trained voices for non-English languages causes pronunciation issues. Always use language-matched voices.
Language Configuration Support for 32+ languages with automatic detection and in-conversation switching.
{
"agent": {
"language": "en" // ISO 639-1 code
}
}
Multi-Language Presets (Different Voice Per Language):
{
"conversation_config": {
"language_presets": [
{
"language": "en",
"voice_id": "en_voice_id",
"first_message": "Hello! How can I help you today?"
},
{
"language": "es",
"voice_id": "es_voice_id",
"first_message": "¡Hola! ¿Cómo puedo ayudarte hoy?"
},
{
"language": "fr",
"voice_id": "fr_voice_id",
"first_message": "Bonjour! Comment puis-je vous aider aujourd'hui?"
}
]
}
}
Automatic Language Detection : Agent detects user's language and switches automatically.
Supported Languages : English, Spanish, French, German, Italian, Portuguese, Dutch, Polish, Arabic, Chinese, Japanese, Korean, Hindi, and 18+ more.
4. Knowledge Base & RAG
RAG (Retrieval-Augmented Generation) Enable agents to access large knowledge bases without loading entire documents into context.
Upload documents (PDF, TXT, DOCX) to knowledge base
ElevenLabs automatically computes vector embeddings
During conversation, relevant chunks retrieved based on semantic similarity
LLM uses retrieved context to generate responses
{
"agent": {
"prompt": {
"knowledge_base": ["doc_id_1", "doc_id_2"]
}
}
}
Upload Documents via API :
import { ElevenLabsClient } from 'elevenlabs';
const client = new ElevenLabsClient({ apiKey: process.env.ELEVENLABS_API_KEY });
// Upload document
const doc = await client.knowledgeBase.upload({
file: fs.createReadStream('support_docs.pdf'),
name: 'Support Documentation'
});
// Compute RAG index
await client.knowledgeBase.computeRagIndex({
document_id: doc.id,
embedding_model: 'e5_mistral_7b' // or 'multilingual_e5_large'
});
{
"knowledge_base_config": {
"max_chunks": 5, // Number of chunks to retrieve
"vector_distance_threshold": 0.8 // Similarity threshold
}
}
Product documentation agents
Customer support (FAQ, help center)
Educational tutors (textbooks, lecture notes)
Healthcare assistants (medical guidelines)
RAG adds ~500ms latency per query
More chunks = higher cost but better context
Higher vector distance = more context but potentially less relevant
Documents must be indexed before use (can take minutes for large docs)
5. Tools (4 Types) ElevenLabs supports 4 distinct tool types, each with different execution patterns.
A. Client Tools Execute operations on the client side (browser or mobile app).
Update UI elements (shopping cart, notifications)
Trigger navigation (redirect user to page)
Access local storage
Control media playback
import { useConversation } from '@elevenlabs/react';
import { z } from 'zod';
const { startConversation } = useConversation({
clientTools: {
updateCart: {
description: "Update the shopping cart with new items",
parameters: z.object({
item: z.string().describe("The item name"),
quantity: z.number().describe("Quantity to add")
}),
handler: async ({ item, quantity }) => {
// Client-side logic
const cart = getCart();
cart.add(item, quantity);
updateUI(cart);
return { success: true, total: cart.total };
}
},
navigate: {
description: "Navigate to a different page",
parameters: z.object({
url: z.string().describe("The URL to navigate to")
}),
handler: async ({ url }) => {
window.location.href = url;
return { success: true };
}
}
}
});
Tool names are case-sensitive
Must return a value (agent reads the return value)
Handler can be async
B. Server Tools (Webhooks) Make HTTP requests to external APIs from ElevenLabs servers.
Fetch real-time data (weather, stock prices)
Update CRM systems (Salesforce, HubSpot)
Process payments (Stripe, PayPal)
Send emails/SMS (SendGrid, Twilio)
elevenlabs tools add-webhook "Get Weather" --config-path tool_configs/get-weather.json
tool_configs/get-weather.json :
{
"name": "get_weather",
"description": "Fetch current weather for a city",
"url": "https://api.weather.com/v1/current",
"method": "GET",
"parameters": {
"type": "object",
"properties": {
"city": {
"type": "string",
"description": "The city name (e.g., 'London', 'New York')"
}
},
"required": ["city"]
},
"headers": {
"Authorization": "Bearer {{secret__weather_api_key}}"
}
}
Dynamic Variables in Tools :
{
"url": "https://api.crm.com/customers/{{user_id}}",
"headers": {
"X-API-Key": "{{secret__crm_api_key}}"
}
}
Secret variables only work in headers (not URL or body)
Schema description guides LLM on when to use tool
C. MCP Tools (Model Context Protocol) Connect to external MCP servers for standardized tool access.
Access databases (PostgreSQL, MongoDB)
Query knowledge bases (Pinecone, Weaviate)
Integrate with IDEs (VS Code, Cursor)
Connect to data sources (Google Drive, Notion)
Navigate to MCP server integrations in dashboard
Click "Add Custom MCP Server"
Configure:
Name : Server identifierServer URL : SSE or HTTP endpointSecret Token : Optional auth header
Test connectivity and discover tools
Add to agents (public or private)
Always Ask : Maximum security, requires permission per tool callFine-Grained : Per-tool approval settingsNo Approval : Auto-execute all tools
Only SSE and HTTP streamable transport supported
MCP servers must be publicly accessible or behind auth
Not available for Zero Retention Mode
Not compatible with HIPAA compliance
Example: Using ElevenLabs MCP Server in Claude Desktop :
{
"mcpServers": {
"ElevenLabs": {
"command": "uvx",
"args": ["elevenlabs-mcp"],
"env": {
"ELEVENLABS_API_KEY": "<your-key>",
"ELEVENLABS_MCP_OUTPUT_MODE": "files"
}
}
}
}
D. System Tools Modify the internal state of the conversation without external calls.
Update conversation context
Switch between workflow nodes
Modify agent behavior mid-conversation
Track conversation state
end_call - End the conversationdetect_language - Detect user's languagetransfer_agent - Switch to different agent/workflow nodetransfer_to_number - Transfer to external phone number (telephony only)dtmf_playpad - Display DTMF keypad (telephony only)voicemail_detection - Detect voicemail (telephony only) {
"system_tools": [
{
"name": "update_conversation_state",
"description": "Update the conversation context with new information",
"parameters": {
"key": { "type": "string" },
"value": { "type": "string" }
}
}
]
}
System tools don't trigger external APIs
Changes are ephemeral (lost after conversation ends)
Useful for workflows and state management
6. SDK Integration
React SDK (@elevenlabs/react) npm install @elevenlabs/react zod
import { useConversation } from '@elevenlabs/react';
import { z } from 'zod';
import { useState } from 'react';
export default function VoiceAgent() {
const [transcript, setTranscript] = useState<string[]>([]);
const {
startConversation,
stopConversation,
status,
isSpeaking
} = useConversation({
agentId: 'your-agent-id',
// Authentication (choose one)
apiKey: process.env.NEXT_PUBLIC_ELEVENLABS_API_KEY,
// Client tools
clientTools: {
updateCart: {
description: "Update shopping cart",
parameters: z.object({
item: z.string(),
quantity: z.number()
}),
handler: async ({ item, quantity }) => {
console.log('Cart updated:', item, quantity);
return { success: true };
}
}
},
// Events
onConnect: () => {
console.log('Connected to agent');
setTranscript([]);
},
onDisconnect: () => console.log('Disconnected'),
onEvent: (event) => {
if (event.type === 'transcript') {
setTranscript(prev => [...prev, `User: ${event.data.text}`]);
} else if (event.type === 'agent_response') {
setTranscript(prev => [...prev, `Agent: ${event.data.text}`]);
}
},
onError: (error) => console.error('Error:', error),
// Regional compliance
serverLocation: 'us'
});
return (
<div>
<div>
<button onClick={startConversation} disabled={status === 'connected'}>
Start Conversation
</button>
<button onClick={stopConversation} disabled={status !== 'connected'}>
Stop
</button>
</div>
<div>Status: {status}</div>
<div>{isSpeaking && 'Agent is speaking...'}</div>
<div>
<h3>Transcript</h3>
{transcript.map((line, i) => (
<p key={i}>{line}</p>
))}
</div>
</div>
);
}
JavaScript SDK (@elevenlabs/client) For vanilla JavaScript projects (no React).
npm install @elevenlabs/client
import { Conversation } from '@elevenlabs/client';
const conversation = new Conversation({
agentId: 'your-agent-id',
apiKey: process.env.ELEVENLABS_API_KEY,
onConnect: () => console.log('Connected'),
onDisconnect: () => console.log('Disconnected'),
onEvent: (event) => {
switch (event.type) {
case 'transcript':
document.getElementById('user-text').textContent = event.data.text;
break;
case 'agent_response':
document.getElementById('agent-text').textContent = event.data.text;
break;
}
}
});
// Start conversation
document.getElementById('start-btn').addEventListener('click', async () => {
await conversation.start();
});
// Stop conversation
document.getElementById('stop-btn').addEventListener('click', async () => {
await conversation.stop();
});
Connection Types: WebRTC vs WebSocket ElevenLabs SDKs support two connection types with different characteristics.
Feature WebSocket WebRTC Authentication signedUrlconversationTokenAudio Format Configurable PCM_48000 (hardcoded) Sample Rate Configurable (16k, 24k, 48k) 48000 (hardcoded) Latency Standard Lower Device Switching Flexible Limited (format locked) Best For General use, flexibility Low-latency requirements
WebSocket Configuration (default):
import { useConversation } from '@elevenlabs/react';
const { startConversation } = useConversation({
agentId: 'your-agent-id',
// WebSocket uses signed URL
signedUrl: async () => {
const response = await fetch('/api/elevenlabs/auth');
const { signedUrl } = await response.json();
return signedUrl;
},
// Connection type (optional, defaults to 'websocket')
connectionType: 'websocket',
// Audio config (flexible)
audioConfig: {
sampleRate: 24000, // 16000, 24000, or 48000
format: 'PCM_24000'
}
});
const { startConversation } = useConversation({
agentId: 'your-agent-id',
// WebRTC uses conversation token (different auth flow)
conversationToken: async () => {
const response = await fetch('/api/elevenlabs/token');
const { token } = await response.json();
return token;
},
// Connection type
connectionType: 'webrtc',
// Audio format is HARDCODED to PCM_48000 (not configurable)
// audioConfig ignored for WebRTC
});
// WebSocket signed URL (GET /v1/convai/conversation/get-signed-url)
app.get('/api/elevenlabs/auth', async (req, res) => {
const response = await fetch(
`https://api.elevenlabs.io/v1/convai/conversation/get-signed-url?agent_id=${AGENT_ID}`,
{ headers: { 'xi-api-key': ELEVENLABS_API_KEY } }
);
const { signed_url } = await response.json();
res.json({ signedUrl: signed_url });
});
// WebRTC conversation token (GET /v1/convai/conversation/token)
app.get('/api/elevenlabs/token', async (req, res) => {
const response = await fetch(
`https://api.elevenlabs.io/v1/convai/conversation/token?agent_id=${AGENT_ID}`,
{ headers: { 'xi-api-key': ELEVENLABS_API_KEY } }
);
const { conversation_token } = await response.json();
res.json({ token: conversation_token });
});
Use WebSocket When Use WebRTC When Need flexible audio formats Need lowest possible latency Switching between audio devices frequently Audio format can be locked to 48kHz Standard latency is acceptable Building real-time applications Need maximum configuration control Performance is critical
WebRTC hardcodes PCM_48000 - no way to change format
Device switching in WebRTC limited by fixed format
Different authentication methods (signedUrl vs conversationToken)
WebRTC may have better performance but less flexibility
React Native SDK (Expo) npx expo install @elevenlabs/react-native @livekit/react-native @livekit/react-native-webrtc livekit-client
Expo SDK 47+
iOS 14.0+ / macOS 11.0+
Custom dev build required (Expo Go not supported) import { useConversation } from '@elevenlabs/react-native';
import { View, Button, Text } from 'react-native';
import { z } from 'zod';
export default function App() {
const { startConversation, stopConversation, status } = useConversation({
agentId: 'your-agent-id',
signedUrl: 'https://api.elevenlabs.io/v1/convai/auth/...',
clientTools: {
updateProfile: {
description: "Update user profile",
parameters: z.object({
name: z.string()
}),
handler: async ({ name }) => {
console.log('Updating profile:', name);
return { success: true };
}
}
}
});
return (
<View style={{ padding: 20 }}>
<Button title="Start" onPress={startConversation} />
<Button title="Stop" onPress={stopConversation} />
<Text>Status: {status}</Text>
</View>
);
}
Requires custom dev build (not Expo Go)
iOS/macOS only (Android support via Kotlin SDK, not yet officially released)
Swift SDK (iOS/macOS) Installation (Swift Package Manager):
dependencies: [
.package(url: "https://github.com/elevenlabs/elevenlabs-swift-sdk", from: "1.0.0")
]
iOS 14.0+ / macOS 11.0+
Swift 5.9+
Native iOS apps
macOS applications
watchOS (with limitations)
Widget (Embeddable Web Component) Installation :
Copy-paste embed code from dashboard or use this template:
<script src="https://elevenlabs.io/convai-widget/index.js"></script>
<script>
ElevenLabsWidget.init({
agentId: 'your-agent-id',
// Theming
theme: {
primaryColor: '#3B82F6',
backgroundColor: '#1F2937',
textColor: '#F9FAFB'
},
// Position
position: 'bottom-right', // 'bottom-left' | 'bottom-right'
// Custom branding
branding: {
logo: 'https://example.com/logo.png',
name: 'Support Agent'
}
});
</script>
Customer support chat bubbles
Website assistants
Lead capture forms
Scribe (Real-Time Speech-to-Text) Status : Closed Beta (requires sales contact)
Release : 2025
Scribe is ElevenLabs' real-time speech-to-text service for low-latency transcription.
Microphone streaming (real-time transcription)
Pre-recorded audio file transcription
Partial (interim) and final transcripts
Word-level timestamps
Voice Activity Detection (VAD)
Manual and automatic commit strategies
Language detection
PCM_16000 and PCM_24000 audio formats
Authentication :
Uses single-use tokens (not API keys):
// Fetch token from backend
const response = await fetch('/api/scribe/token');
const { token } = await response.json();
// Backend endpoint
const token = await client.scribe.getToken();
return { token };
import { useScribe } from '@elevenlabs/react';
export default function Transcription() {
const {
connect,
disconnect,
startRecording,
stopRecording,
status,
transcript,
partialTranscript
} = useScribe({
token: async () => {
const response = await fetch('/api/scribe/token');
const { token } = await response.json();
return token;
},
// Commit strategy
commitStrategy: 'vad', // 'vad' (automatic) or 'manual'
// Audio format
sampleRate: 16000, // 16000 or 24000
// Events
onConnect: () => console.log('Connected to Scribe'),
onDisconnect: () => console.log('Disconnected'),
onPartialTranscript: (text) => {
console.log('Interim:', text);
},
onFinalTranscript: (text, timestamps) => {
console.log('Final:', text);
console.log('Timestamps:', timestamps); // Word-level timing
},
onError: (error) => console.error('Error:', error)
});
return (
<div>
<button onClick={connect}>Connect</button>
<button onClick={startRecording}>Start Recording</button>
<button onClick={stopRecording}>Stop Recording</button>
<button onClick={disconnect}>Disconnect</button>
<p>Status: {status}</p>
<p>Partial: {partialTranscript}</p>
<p>Final: {transcript}</p>
</div>
);
}
JavaScript SDK (Scribe.connect) :
import { Scribe } from '@elevenlabs/client';
const connection = await Scribe.connect({
token: 'your-single-use-token',
sampleRate: 16000,
commitStrategy: 'vad',
onPartialTranscript: (text) => {
document.getElementById('interim').textContent = text;
},
onFinalTranscript: (text, timestamps) => {
const finalDiv = document.getElementById('final');
finalDiv.textContent += text + ' ';
// timestamps: [{ word: 'hello', start: 0.5, end: 0.8 }, ...]
},
onError: (error) => {
console.error('Scribe error:', error);
}
});
// Start recording from microphone
await connection.startRecording();
// Stop recording
await connection.stopRecording();
// Manual commit (if commitStrategy: 'manual')
await connection.commit();
// Disconnect
await connection.disconnect();
Transcribing Pre-Recorded Files :
import { Scribe } from '@elevenlabs/client';
const connection = await Scribe.connect({ token });
// Send audio buffer
const audioBuffer = fs.readFileSync('recording.pcm');
await connection.sendAudioData(audioBuffer);
// Manually commit to get final transcript
await connection.commit();
// Wait for final transcript event
SESSION_STARTED: Connection establishedPARTIAL_TRANSCRIPT: Interim transcription (unbuffered)FINAL_TRANSCRIPT: Complete sentence/phraseFINAL_TRANSCRIPT_WITH_TIMESTAMPS: Final + word timingERROR: Transcription errorAUTH_ERROR: Authentication failedOPEN: WebSocket openedCLOSE: WebSocket closed Strategy Description Use When vad (automatic)Voice Activity Detection auto-commits on silence Real-time transcription manualCall connection.commit() explicitly Pre-recorded files, controlled commits
PCM_16000 (16kHz, 16-bit PCM)PCM_24000 (24kHz, 16-bit PCM)
Token is single-use (expires after one connection)
Closed beta - requires sales contact
Language detection automatic (no manual override)
No speaker diarization yet
Building custom transcription UI
Real-time captions/subtitles
Voice note apps
Meeting transcription
Accessibility features
When NOT to Use :
Use Agents Platform instead if you need:
Conversational AI (LLM + TTS)
Two-way voice interaction
Agent responses
7. Testing & Evaluation
Scenario Testing (LLM-Based Evaluation) Simulate full conversations and evaluate against success criteria.
elevenlabs tests add "Refund Request Test" --template basic-llm
test_configs/refund-request-test.json :
{
"name": "Refund Request Test",
"scenario": "Customer requests refund for defective product",
"user_input": "I want a refund for order #12345. The product was broken when it arrived.",
"success_criteria": [
"Agent acknowledges the request empathetically",
"Agent asks for order number (which was already provided)",
"Agent verifies order details",
"Agent provides refund timeline or next steps"
],
"evaluation_type": "llm"
}
elevenlabs agents test "Support Agent"
Tool Call Testing Verify that agents correctly use tools with the right parameters.
{
"name": "Account Balance Test",
"scenario": "Customer requests account balance",
"expected_tool_call": {
"tool_name": "get_account_balance",
"parameters": {
"account_id": "ACC-12345"
}
}
}
Load Testing Test agent capacity under high concurrency.
# Spawn 100 users, 1 per second, test for 10 minutes
elevenlabs test load \
--users 100 \
--spawn-rate 1 \
--duration 600
Load testing consumes real API credits
Use burst pricing for expected traffic spikes
Requires careful planning to avoid hitting rate limits
Simulation API (Programmatic Testing) POST /v1/convai/agents/:agent_id/simulate
const simulation = await client.agents.simulate({
agent_id: 'agent_123',
scenario: 'Customer requests refund',
user_messages: [
"I want a refund for order #12345",
"I ordered it last week",
"Yes, please process it"
],
success_criteria: [
"Agent acknowledges request",
"Agent asks for order details",
"Agent provides refund timeline"
]
});
console.log('Test passed:', simulation.passed);
console.log('Criteria met:', simulation.evaluation.criteria_met);
CI/CD integration (test before deploy)
Regression testing
Load testing preparation
8. Analytics & Monitoring
Conversation Analysis Extract structured data from conversation transcripts.
Success Evaluation (LLM-Based) {
"evaluation_criteria": {
"resolution": "Was the customer's issue resolved?",
"sentiment": "Was the conversation tone positive?",
"compliance": "Did the agent follow company policies?"
}
}
Data Collection {
"data_collection": {
"fields": [
{ "name": "customer_name", "type": "string" },
{ "name": "issue_type", "type": "enum", "values": ["billing", "technical", "other"] },
{ "name": "satisfaction", "type": "number", "range": [1, 5] }
]
}
}
Via Post-call Webhooks (real-time)
Via Analytics Dashboard (batch)
Via API (on-demand)
Analytics Dashboard
Resolution Rates : % of issues resolvedCX Metrics : Sentiment, satisfaction, CSATCompliance : Policy adherence, guardrail violationsPerformance : Response time, call duration, concurrencyTool Usage : Tool call frequency, success ratesLLM Costs : Track costs per agent/conversation Access : Dashboard → Analytics tab
9. Privacy & Compliance
Data Retention Default : 2 years (GDPR-compliant)
{
"privacy": {
"transcripts": {
"retention_days": 730 // 2 years (GDPR)
},
"audio": {
"retention_days": 2190 // 6 years (HIPAA)
}
}
}
Compliance Recommendations :
GDPR : Align with data processing purposes (typically 1-2 years)HIPAA : Minimum 6 years for medical recordsSOC 2 : Encryption in transit and at rest (automatic)
Encryption
In Transit : TLS 1.3At Rest : AES-256Regional Compliance : Data residency (US, EU, India) const { startConversation } = useConversation({
serverLocation: 'eu-residency' // 'us' | 'global' | 'eu-residency' | 'in-residency'
});
Zero Retention Mode For maximum privacy, enable zero retention to immediately delete all conversation data.
No conversation history
No analytics
No post-call webhooks
No MCP tool integrations
10. Cost Optimization
LLM Caching Reduce costs by caching repeated inputs.
First request : Full cost (input_cache_write)Subsequent requests : Reduced cost (input_cache_read)Automatic cache invalidation after TTL {
"llm_config": {
"caching": {
"enabled": true,
"ttl_seconds": 3600 // 1 hour
}
}
}
Repeated system prompts
Large knowledge bases
Frequent tool definitions
Savings : Up to 90% on cached inputs
Model Swapping Switch between models based on cost/performance needs.
GPT-4o (high cost, high quality)GPT-4o-mini (medium cost, good quality)Claude Sonnet 4.5 (high cost, best reasoning)Gemini 2.5 Flash (low cost, fast) {
"llm_config": {
"model": "gpt-4o-mini" // Swap anytime via dashboard or API
}
}
Burst Pricing Temporarily exceed concurrency limits during high-demand periods.
Normal : Your subscription concurrency limit (e.g., 10 simultaneous calls)Burst : Up to 3x your limit (e.g., 30 simultaneous calls)Cost : 2x the standard rate for burst calls {
"call_limits": {
"burst_pricing_enabled": true
}
}
Black Friday traffic spikes
Product launches
Seasonal demand (holidays)
Burst calls cost 2x (plan accordingly)
Not unlimited (3x cap)
11. Advanced Features
Events (WebSocket/SSE) Real-time event streaming for live transcription, agent responses, and tool calls.
audio - Audio stream chunkstranscript - Real-time transcriptionagent_response - Agent's text responsetool_call - Tool execution statusconversation_state - State updates const { startConversation } = useConversation({
onEvent: (event) => {
switch (event.type) {
case 'transcript':
console.log('User said:', event.data.text);
break;
case 'agent_response':
console.log('Agent replied:', event.data.text);
break;
case 'tool_call':
console.log('Tool called:', event.data.tool_name);
break;
}
}
});
Custom Models (Bring Your Own LLM) Use your own OpenAI API key or custom LLM server.
{
"llm_config": {
"custom": {
"endpoint": "https://api.openai.com/v1/chat/completions",
"api_key": "{{secret__openai_api_key}}",
"model": "gpt-4"
}
}
}
Custom fine-tuned models
Private LLM deployments (Ollama, LocalAI)
Cost control (use your own credits)
Compliance (on-premise models)
Endpoint must be OpenAI-compatible
No official support for non-OpenAI-compatible models
Post-Call Webhooks Receive notifications when a call ends and analysis completes.
{
"webhooks": {
"post_call": {
"url": "https://api.example.com/webhook",
"headers": {
"Authorization": "Bearer {{secret__webhook_auth_token}}"
}
}
}
}
{
"conversation_id": "conv_123",
"agent_id": "agent_456",
"transcript": "...",
"duration_seconds": 120,
"analysis": {
"sentiment": "positive",
"resolution": true,
"extracted_data": {
"customer_name": "John Doe",
"issue_type": "billing"
}
}
}
Security (HMAC Verification) :
import crypto from 'crypto';
export async function POST(req: Request) {
const signature = req.headers.get('elevenlabs-signature');
const payload = await req.text();
const hmac = crypto
.createHmac('sha256', process.env.WEBHOOK_SECRET!)
.update(payload)
.digest('hex');
if (signature !== hmac) {
return new Response('Invalid signature', { status: 401 });
}
// Process webhook
const data = JSON.parse(payload);
console.log('Conversation ended:', data.conversation_id);
// MUST return 200
return new Response('OK', { status: 200 });
}
Must return 200 status code
Auto-disabled after 10 consecutive failures (7+ days since last success)
Retry logic: 3 attempts with exponential backoff
Chat Mode (Text-Only) Disable voice, use text-only conversations.
{
"conversation_config": {
"chat_mode": true // Disables audio input/output
}
}
Faster response times (~200ms saved)
Lower costs (no ASR/TTS charges)
Easier testing (no microphone required)
Testing agents without audio
Building text chat interfaces
Accessibility (text-only users)
Telephony Integration SIP Endpoint: sip-static.rtc.elevenlabs.io
TLS Transport: Recommended for production
SRTP Encryption: Supported
Supported Providers : Twilio, Vonage, RingCentral, Sinch, Infobip, Telnyx, Exotel, Plivo, Bandwidth
Native Twilio Integration :
{
"telephony": {
"provider": "twilio",
"phone_number": "+1234567890",
"account_sid": "{{secret__twilio_account_sid}}",
"auth_token": "{{secret__twilio_auth_token}}"
}
}
Customer support hotlines
Appointment scheduling
Order status inquiries
IVR systems
12. CLI & DevOps ("Agents as Code")
Installation & Authentication # Install globally
npm install -g @elevenlabs/cli
# Authenticate
elevenlabs auth login
# Set residency (for GDPR compliance)
elevenlabs auth residency eu-residency # or 'in-residency' | 'global'
# Check current user
elevenlabs auth whoami
Environment Variables (For CI/CD):
export ELEVENLABS_API_KEY=your-api-key
Project Structure Directory Structure Created :
your_project/
├── agents.json # Agent registry
├── tools.json # Tool configurations
├── tests.json # Test configurations
├── agent_configs/ # Individual agent files (.json)
├── tool_configs/ # Tool configuration files
└── test_configs/ # Test configuration files
Agent Management Commands # Create agent
elevenlabs agents add "Support Agent" --template customer-service
# Deploy to platform
elevenlabs agents push
elevenlabs agents push --agent "Support Agent"
elevenlabs agents push --env prod
elevenlabs agents push --dry-run # Preview changes
# Import existing agents
elevenlabs agents pull
# List agents
elevenlabs agents list
# Check sync status
elevenlabs agents status
# Delete agent
elevenlabs agents delete <agent_id>
Tool Management Commands # Create webhook tool
elevenlabs tools add-webhook "Get Weather" --config-path tool_configs/get-weather.json
# Create client tool
elevenlabs tools add-client "Update Cart" --config-path tool_configs/update-cart.json
# Deploy tools
elevenlabs tools push
# Import existing tools
elevenlabs tools pull
# Delete tools
elevenlabs tools delete <tool_id>
elevenlabs tools delete --all
Testing Commands # Create test
elevenlabs tests add "Refund Test" --template basic-llm
# Deploy tests
elevenlabs tests push
# Import tests
elevenlabs tests pull
# Run test
elevenlabs agents test "Support Agent"
Multi-Environment Deployment # Development
elevenlabs agents push --env dev
# Staging
elevenlabs agents push --env staging
# Production (with confirmation)
elevenlabs agents push --env prod --dry-run
# Review changes...
elevenlabs agents push --env prod
Environment-Specific Configs :
agent_configs/
├── support-bot.json # Base config
├── support-bot.dev.json # Dev overrides
├── support-bot.staging.json # Staging overrides
└── support-bot.prod.json # Prod overrides
CI/CD Integration name: Deploy Agent
on:
push:
branches: [main]
paths:
- 'agent_configs/**'
- 'tool_configs/**'
jobs:
deploy:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Install CLI
run: npm install -g @elevenlabs/cli
- name: Test Configs
run: elevenlabs agents push --dry-run --env prod
env:
ELEVENLABS_API_KEY: ${{ secrets.ELEVENLABS_API_KEY_PROD }}
- name: Deploy
run: elevenlabs agents push --env prod
env:
ELEVENLABS_API_KEY: ${{ secrets.ELEVENLABS_API_KEY_PROD }}
Version Control Best Practices
agent_configs/*.jsontool_configs/*.jsontest_configs/*.jsonagents.json, tools.json, tests.json # .gitignore
.env
.elevenlabs/
*.secret.json
13. Common Errors & Solutions
Error 1: Missing Required Dynamic Variables Symptom : "Missing required dynamic variables" error, no transcript generated
Cause : Dynamic variables referenced in prompts/messages but not provided at conversation start
const conversation = await client.conversations.create({
agent_id: "agent_123",
dynamic_variables: {
user_name: "John",
account_tier: "premium",
// Provide ALL variables referenced in prompts
}
});
Error 2: Case-Sensitive Tool Names Symptom : Tool not executing, agent says "tool not found"
Cause : Tool name in config doesn't match registered name (case-sensitive)
// agent_configs/bot.json
{
"agent": {
"prompt": {
"tool_ids": ["orderLookup"] // Must match exactly
}
}
}
// tool_configs/order-lookup.json
{
"name": "orderLookup" // Match case exactly
}
Error 3: Webhook Authentication Failures Symptom : Webhook auto-disabled after failures
Incorrect HMAC signature verification
Not returning 200 status code
10+ consecutive failures
// Always verify HMAC signature
import crypto from 'crypto';
const signature = req.headers['elevenlabs-signature'];
const payload = JSON.stringify(req.body);
const hmac = crypto
.createHmac('sha256', process.env.WEBHOOK_SECRET)
.update(payload)
.digest('hex');
if (signature !== hmac) {
return res.status(401).json({ error: 'Invalid signature' });
}
// Process webhook
// ...
// MUST return 200
res.status(200).json({ success: true });
Error 4: Voice Consistency Issues Symptom : Generated audio varies in volume/tone
Background noise in voice clone training data
Inconsistent microphone distance
Whispering or shouting in samples
Use clean audio samples (no music, noise, pops)
Maintain consistent microphone distance
Avoid extreme volumes
Test voice settings before deployment
Error 5: Wrong Language Voice Symptom : Unpredictable pronunciation, accent issues
Cause : Using English-trained voice for non-English language
{
"language_presets": [
{
"language": "es",
"voice_id": "spanish_trained_voice_id" // Must be Spanish-trained
}
]
}
Error 6: Restricted API Keys Not Supported (CLI) Symptom : CLI authentication fails
Cause : Using restricted API key (not currently supported)
Solution : Use unrestricted API key for CLI operations
Error 7: Agent Configuration Push Conflicts Symptom : Changes not reflected after push
Cause : Hash-based change detection missed modification
# Force re-sync
elevenlabs agents init --override
elevenlabs agents pull # Re-import from platform
# Make changes
elevenlabs agents push
Error 8: Tool Parameter Schema Mismatch Symptom : Tool called but parameters empty or incorrect
Cause : Schema definition doesn't match actual usage
// tool_configs/order-lookup.json
{
"parameters": {
"type": "object",
"properties": {
"order_id": {
"type": "string",
"description": "The order ID to look up (format: ORD-12345)" // Clear description
}
},
"required": ["order_id"]
}
}
Error 9: RAG Index Not Ready Symptom : Agent doesn't use knowledge base
Cause : RAG index still computing (can take minutes for large documents)
// Check index status before using
const index = await client.knowledgeBase.getRagIndex({
document_id: 'doc_123'
});
if (index.status !== 'ready') {
console.log('Index still computing...');
}
Error 10: WebSocket Protocol Error (1002) Symptom : Intermittent "protocol error" when using WebSocket connections
Cause : Network instability or incompatible browser
Use WebRTC instead of WebSocket (more resilient)
Implement reconnection logic
Check browser compatibility
Error 11: 401 Unauthorized in Production Symptom : Works locally but fails in production
Cause : Agent visibility settings or API key configuration
Check agent visibility (public vs private)
Verify API key is set in production environment
Check allowlist configuration if enabled
Error 12: Allowlist Connection Errors Symptom : "Host elevenlabs.io is not allowed to connect to this agent"
Cause : Agent has allowlist enabled but using shared link
Configure agent allowlist with correct domains
Or disable allowlist for testing
Error 13: Workflow Infinite Loops Symptom : Agent gets stuck in workflow, never completes
Cause : Edge conditions creating loops
Add max iteration limits
Test all edge paths
Add explicit exit conditions
Error 14: Burst Pricing Not Enabled Symptom : Calls rejected during traffic spikes
Cause : Burst pricing not enabled in agent settings
{
"call_limits": {
"burst_pricing_enabled": true
}
}
Error 15: MCP Server Timeout Symptom : MCP tools not responding
Cause : MCP server slow or unreachable
Check MCP server URL is accessible
Verify transport type (SSE vs HTTP)
Check authentication token
Monitor MCP server logs
Error 16: First Message Cutoff on Android Symptom : First message from agent gets cut off on Android devices (works fine on iOS/web)
Cause : Android devices need time to switch to correct audio mode after connection
import { useConversation } from '@elevenlabs/react';
const { startConversation } = useConversation({
agentId: 'your-agent-id',
// Add connection delay for Android
connectionDelay: {
android: 3_000, // 3 seconds (default)
ios: 0, // No delay needed
default: 0 // Other platforms
},
// Rest of config...
});
Android needs 3 seconds to switch audio routing mode
Without delay, first audio chunk is lost
iOS and web don't have this issue
Adjust delay if 3 seconds isn't sufficient
# Test on Android device
npm run android
# First message should now be complete
Error 17: CSP (Content Security Policy) Violations Symptom : "Refused to load the script because it violates the following Content Security Policy directive" errors in browser console
Cause : Applications with strict Content Security Policy don't allow data: or blob: URLs in script-src directive. ElevenLabs SDK uses Audio Worklets that are loaded as blobs by default.
Solution - Self-Host Worklet Files :
Step 1 : Copy worklet files to your public directory:
# Copy from node_modules
cp node_modules/@elevenlabs/client/dist/worklets/*.js public/elevenlabs/
Step 2 : Configure SDK to use self-hosted worklets:
import { useConversation } from '@elevenlabs/react';
const { startConversation } = useConversation({
agentId: 'your-agent-id',
// Point to self-hosted worklet files
workletPaths: {
'rawAudioProcessor': '/elevenlabs/rawAudioProcessor.worklet.js',
'audioConcatProcessor': '/elevenlabs/audioConcatProcessor.worklet.js',
},
// Rest of config...
});
Step 3 : Update CSP headers to allow self-hosted scripts:
# nginx example
add_header Content-Security-Policy "
default-src 'self';
script-src 'self' https://elevenlabs.io;
connect-src 'self' https://api.elevenlabs.io wss://api.elevenlabs.io;
worker-src 'self';
" always;
node_modules/@elevenlabs/client/dist/worklets/
├── rawAudioProcessor.worklet.js
└── audioConcatProcessor.worklet.js
Worklet files must be served from same origin (CORS restriction)
Update worklet files when upgrading @elevenlabs/client
Paths must match exactly (case-sensitive)
Enterprise applications with strict CSP
Government/financial apps
Apps with security audits
Any app blocking blob: URLs
Integration with Existing Skills This skill composes well with:
cloudflare-worker-base → Deploy agents on Cloudflare Workers edge networkcloudflare-workers-ai → Use Cloudflare LLMs as custom models in agentscloudflare-durable-objects → Persistent conversation state and session managementcloudflare-kv → Cache agent configurations and user preferencesnextjs → React SDK integration in Next.js applicationsai-sdk-core → Vercel AI SDK provider for unified AI interfaceclerk-auth → Authenticated voice sessions with user identityhono-routing → API routes for webhooks and server tools
Additional Resources
Production Tested : WordPress Auditor, Customer Support Agents
Last Updated : 2025-11-03
Package Versions : elevenlabs@1.59.0, @elevenlabs/cli@0.2.0
