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agents Build voice AI agents with ElevenLabs. Use when creating voice assistants, customer service bots, interactive voice characters, or any real-time voice conversation experience.
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6 fichiers name agents description Build voice AI agents with ElevenLabs. Use when creating voice assistants, customer service bots, interactive voice characters, or any real-time voice conversation experience. license MIT compatibility Requires internet access and an ElevenLabs API key (ELEVENLABS_API_KEY). metadata {"openclaw":{"requires":{"env":["ELEVENLABS_API_KEY"]},"primaryEnv":"ELEVENLABS_API_KEY"}}
ElevenLabs Agents Platform
Build voice AI agents with natural conversations, multiple LLM providers, custom tools, and easy web embedding.
Setup: See Installation Guide for CLI and SDK setup.
Quick Start with CLI
The ElevenLabs CLI is the recommended way to create and manage agents:
npm install -g @elevenlabs/cli
elevenlabs auth login
elevenlabs agents init
elevenlabs agents add "My Assistant" --template default
elevenlabs agents push
Available templates:
default
minimal
voice-only
text-only
customer-service
assistant
Python from elevenlabs.client import ElevenLabs
client = ElevenLabs()
agent = client.conversational_ai.agents.create(
name="My Assistant" ,
conversation_config={
"agent" : {"first_message" : "Hello! How can I help?" , "language" : "en" },
"tts" : {"voice_id" : "JBFqnCBsd6RMkjVDRZzb" }
},
prompt={
"prompt" : "You are a helpful assistant. Be concise and friendly." ,
"llm" : "gpt-4o-mini" ,
"temperature" : 0.7
}
)
JavaScript import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js" ;
const client = new ElevenLabsClient ();
const agent = await client.conversationalAi .agents .create ({
name : "My Assistant" ,
conversationConfig : {
agent : { firstMessage : "Hello! How can I help?" , language : "en" },
tts : { voiceId : "JBFqnCBsd6RMkjVDRZzb" }
},
prompt : { prompt : "You are a helpful assistant." , llm : "gpt-4o-mini" , temperature : 0.7 }
});
cURL curl -X POST "https://api.elevenlabs.io/v1/convai/agents/create" \
-H "xi-api-key: $ELEVENLABS_API_KEY " -H "Content-Type: application/json" \
-d '{"name": "My Assistant", "conversation_config": {"agent": {"first_message": "Hello!", "language": "en"}, "tts": {"voice_id": "JBFqnCBsd6RMkjVDRZzb"}}, "prompt": {"prompt": "You are helpful.", "llm": "gpt-4o-mini"}}'
Starting Conversations Server-side (Python): Get signed URL for client connection:
signed_url = client.conversational_ai.conversations.get_signed_url(agent_id="your-agent-id" )
Client-side (JavaScript):
import { Conversation } from "@elevenlabs/client" ;
const conversation = await Conversation .startSession ({
agentId : "your-agent-id" ,
onMessage : (msg ) => console .log ("Agent:" , msg.message ),
onUserTranscript : (t ) => console .log ("User:" , t.message ),
onError : (e ) => console .error (e)
});
import { useConversation } from "@elevenlabs/react" ;
const conversation = useConversation ({ onMessage : (msg ) => console .log (msg) });
await conversation.startSession ({ signedUrl : token });
Configuration Provider Models OpenAI gpt-4o, gpt-4o-mini, gpt-4-turboAnthropic claude-3-5-sonnet, claude-3-5-haikuGoogle gemini-1.5-pro, gemini-1.5-flashCustom custom-llm (bring your own endpoint)
Popular voices: JBFqnCBsd6RMkjVDRZzb (George), EXAVITQu4vr4xnSDxMaL (Sarah), onwK4e9ZLuTAKqWW03F9 (Daniel), XB0fDUnXU5powFXDhCwa (Charlotte)
Turn-taking modes: server_vad (auto-detect speech end) or turn_based (explicit signals)
Tools Extend agents with webhook, client, or system tools:
tools=[
{"type" : "webhook" , "name" : "get_weather" , "description" : "Get weather" ,
"webhook" : {"url" : "https://api.example.com/weather" , "method" : "POST" },
"parameters" : {"type" : "object" , "properties" : {"location" : {"type" : "string" }}, "required" : ["location" ]}},
{"type" : "system" , "name" : "end_call" },
{"type" : "system" , "name" : "transfer_to_number" , "phone_number" : "+1234567890" }
]
Client tools run in browser:
clientTools : {
show_product : async ({ productId }) => {
document .getElementById ("product" ).src = `/products/${productId} ` ;
return { success : true };
}
}
Widget Embedding <elevenlabs-convai agent-id ="your-agent-id" > </elevenlabs-convai >
<script src ="https://unpkg.com/@elevenlabs/convai-widget-embed" async type ="text/javascript" > </script >
Customize with attributes: avatar-image-url, action-text, start-call-text, end-call-text.
Outbound Calls Make outbound phone calls using your agent via Twilio integration:
Python response = client.conversational_ai.twilio.outbound_call(
agent_id="your-agent-id" ,
agent_phone_number_id="your-phone-number-id" ,
to_number="+1234567890"
)
print (f"Call initiated: {response.conversation_id} " )
JavaScript const response = await client.conversationalAi .twilio .outboundCall ({
agentId : "your-agent-id" ,
agentPhoneNumberId : "your-phone-number-id" ,
toNumber : "+1234567890" ,
});
cURL curl -X POST "https://api.elevenlabs.io/v1/convai/twilio/outbound-call" \
-H "xi-api-key: $ELEVENLABS_API_KEY " -H "Content-Type: application/json" \
-d '{"agent_id": "your-agent-id", "agent_phone_number_id": "your-phone-number-id", "to_number": "+1234567890"}'
Managing Agents
Using CLI (Recommended)
elevenlabs agents list
elevenlabs agents status
elevenlabs agents pull
elevenlabs agents pull --agent <agent-id>
elevenlabs agents push
elevenlabs agents push --dry-run
elevenlabs agents tools add "Weather API" --type webhook --config-path ./weather.json
Project Structure The CLI creates a project structure for managing agents:
your_project/
├── agents.json # Agent definitions
├── tools.json # Tool configurations
├── agent_configs/ # Individual agent configs
└── tool_configs/ # Individual tool configs
SDK Examples
agents = client.conversational_ai.agents.list ()
agent = client.conversational_ai.agents.get(agent_id="your-agent-id" )
client.conversational_ai.agents.update(agent_id="your-agent-id" , name="New Name" )
client.conversational_ai.agents.update(agent_id="your-agent-id" ,
prompt={"prompt" : "New instructions" , "llm" : "claude-3-5-sonnet" })
client.conversational_ai.agents.delete(agent_id="your-agent-id" )
Error Handling try :
agent = client.conversational_ai.agents.create(...)
except Exception as e:
print (f"API error: {e} " )
Common errors: 401 (invalid key), 404 (not found), 422 (invalid config), 429 (rate limit)
References 