This documentation is for developers integrating directly with the ElevenLabs WebSocket API. For convenience, consider using the official SDKs provided by ElevenLabs.
The ElevenLabs Conversational AI WebSocket API enables real-time, interactive voice conversations with AI agents. By establishing a WebSocket connection, you can send audio input and receive audio responses in real-time, creating life-like conversational experiences.
Endpoint: wss://api.elevenlabs.io/v1/convai/conversation?agent_id={agent_id}

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Authentication

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Using Agent ID

For public agents, you can directly use the agent_id in the WebSocket URL without additional authentication: 
wss://api.elevenlabs.io/v1/convai/conversation?agent_id=<your-agent-id>

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Using a Signed URL

For private agents or conversations requiring authorization, obtain a signed URL from your server, which securely communicates with the ElevenLabs API using your API key.

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Example using cURL

Request: 
curl -X GET "https://api.elevenlabs.io/v1/convai/conversation/get_signed_url?agent_id=<your-agent-id>" \
     -H "xi-api-key: <your-api-key>"
Response: 
{
  "signed_url": "wss://api.elevenlabs.io/v1/convai/conversation?agent_id=<your-agent-id>&token=<token>"
}
Never expose your ElevenLabs API key on the client side.

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Communication

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Client-to-Server Messages

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User Audio Chunk

Send audio data from the user to the server. Format: 
{
  "user_audio_chunk": "<base64-encoded-audio-data>"
}
Notes:
  • Audio Format Requirements:
    • PCM 16-bit mono format
    • Base64 encoded
    • Sample rate of 16,000 Hz
  • Recommended Chunk Duration:
    • Send audio chunks approximately every 250 milliseconds (0.25 seconds)
    • This equates to chunks of about 4,000 samples at a 16,000 Hz sample rate
  • Optimizing Latency and Efficiency:
    • Balance Latency and Efficiency: Sending audio chunks every 250 milliseconds offers a good trade-off between responsiveness and network overhead.
    • Adjust Based on Needs:
      • Lower Latency Requirements: Decrease the chunk duration to send smaller chunks more frequently.
      • Higher Efficiency Requirements: Increase the chunk duration to send larger chunks less frequently.
    • Network Conditions: Adapt the chunk size if you experience network constraints or variability.

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Pong Message

Respond to server ping messages by sending a pong message, ensuring the event_id matches the one received in the ping message. Format: 
{
  "type": "pong",
  "event_id": 12345
}

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Conversation Initiation Client Data Override

Send initial conversation configuration to the server with a conversation_initiation_client_data message, optionally including agent prompt overrides, preferred language, TTS voice settings, and custom LLM parameters that will be used for the conversation. Format: 
{
  "type": "conversation_initiation_client_data",
  "conversation_config_override": {
    "agent": {
      "prompt": {
        "prompt": "You are a helpful AI assistant. You are cheerful and friendly."
      },
      "first_message": "Hi! How can I help you today?",
      "language": "en"
    },
    "tts": {
      "voice_id": "pNInz6obpgDQGcFmaJgB"
    }
  },
  "custom_llm_extra_body": {
    "temperature": 0.7,
    "max_tokens": 150
  }
}

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Client Tool Result

Respond to server client_tool_call messages by sending a client_tool_result message, ensuring the tool call id matches the one in the received call message. 
{
  "type": "client_tool_result",
  "tool_call_id": str,
  "result": str,
  "is_error": bool,
}

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Server-to-Client Messages

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conversation_initiation_metadata

Provides initial metadata about the conversation. Format: 
{
  "type": "conversation_initiation_metadata",
  "conversation_initiation_metadata_event": {
    "conversation_id": "conv_123456789",
    "agent_output_audio_format": "pcm_16000"
  }
}

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Other Server-to-Client Messages

TypePurpose
user_transcriptTranscriptions of the user’s speech
agent_responseAgent’s textual response
audioChunks of the agent’s audio response
interruptionIndicates that the agent’s response was interrupted
pingServer pings to measure latency
client_tool_callInitiate client tool call
Message Formats
user_transcript: 
{
  "type": "user_transcript",
  "user_transcription_event": {
    "user_transcript": "Hello, how are you today?"
  }
}
agent_response: 
{
  "type": "agent_response",
  "agent_response_event": {
    "agent_response": "Hello! I'm doing well, thank you for asking. How can I assist you today?"
  }
}
audio: 
{
  "type": "audio",
  "audio_event": {
    "audio_base_64": "SGVsbG8sIHRoaXMgaXMgYSBzYW1wbGUgYXVkaW8gY2h1bms=",
    "event_id": 67890
  }
}
interruption: 
{
  "type": "interruption",
  "interruption_event": {
    "event_id": 54321
  }
}
internal_tentative_agent_response: 
{
  "type": "internal_tentative_agent_response",
  "tentative_agent_response_internal_event": {
    "tentative_agent_response": "I'm thinking about how to respond..."
  }
}
ping: 
{
  "type": "ping",
  "ping_event": {
    "event_id": 13579,
    "ping_ms": 50
  }
}
client_tool_call: 
{
  "type": "client_tool_call",
  "client_tool_call": {
    "tool_name": string,
    "tool_call_id": string,
    "parameters": dict,
  }
}

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Latency Management

To ensure smooth conversations, implement these strategies:
  • Adaptive Buffering: Adjust audio buffering based on network conditions.
  • Jitter Buffer: Implement a jitter buffer to smooth out variations in packet arrival times.
  • Ping-Pong Monitoring: Use ping and pong events to measure round-trip time and adjust accordingly.

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Security Best Practices

  • Rotate API keys regularly and use environment variables to store them.
  • Implement rate limiting to prevent abuse.
  • Clearly explain the intention when prompting users for microphone access.
  • Optimized Chunking: Tweak the audio chunk duration to balance latency and efficiency.

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Additional Resources