--- 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](references/installation.md) for CLI and SDK setup.

## Quick Start with CLI

The ElevenLabs CLI is the recommended way to create and manage agents:

```bash # Install CLI and authenticate npm install -g @elevenlabs/cli elevenlabs auth login

# Initialize project and create an agent elevenlabs agents init elevenlabs agents add "My Assistant" --template complete

# Push to ElevenLabs platform elevenlabs agents push ```

**Available templates:** `complete`, `minimal`, `voice-only`, `text-only`, `customer-service`, `assistant`

### Python

```python from elevenlabs import ElevenLabs

client = ElevenLabs()

agent = client.conversational_ai.agents.create( name="My Assistant", enable_versioning=True, conversation_config={ "agent": { "first_message": "Hello! How can I help?", "language": "en", "prompt": { "prompt": "You are a helpful assistant. Be concise and friendly.", "llm": "gemini-2.0-flash", "temperature": 0.7 } }, "tts": {"voice_id": "JBFqnCBsd6RMkjVDRZzb"} } ) ```

### JavaScript

```javascript import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js"; const client = new ElevenLabsClient();

const agent = await client.conversationalAi.agents.create({ name: "My Assistant", enableVersioning: true, conversationConfig: { agent: { firstMessage: "Hello! How can I help?", language: "en", prompt: { prompt: "You are a helpful assistant.", llm: "gemini-2.0-flash", temperature: 0.7 } }, tts: { voiceId: "JBFqnCBsd6RMkjVDRZzb" } } }); ```

### cURL

```bash curl -X POST "https://api.elevenlabs.io/v1/convai/agents/create?enable_versioning=true" \ -H "xi-api-key: $ELEVENLABS_API_KEY" -H "Content-Type: application/json" \ -d '{"name": "My Assistant", "conversation_config": {"agent": {"first_message": "Hello!", "language": "en", "prompt": {"prompt": "You are helpful.", "llm": "gemini-2.0-flash"}}, "tts": {"voice_id": "JBFqnCBsd6RMkjVDRZzb"}}}' ```

## Starting Conversations

**Server-side (Python):** Get signed URL for client connection: ```python signed_url = client.conversational_ai.conversations.get_signed_url( agent_id="your-agent-id", environment="staging", ) ```

**Client-side (JavaScript):** ```javascript import { Conversation } from "@elevenlabs/client";

const conversation = await Conversation.startSession({ agentId: "your-agent-id", environment: "staging", onMessage: (msg) => console.log("Agent:", msg.message), onUserTranscript: (t) => console.log("User:", t.message), onError: (e) => console.error(e) }); ```

**React Hook:** ```typescript import { useConversation } from "@elevenlabs/react";

const conversation = useConversation({ onMessage: (msg) => console.log(msg) }); // Get a signed URL for the target environment from your backend, then: await conversation.startSession({ signedUrl: token }); ```

## Configuration

| Provider | Models | |----------|--------| | OpenAI | `gpt-5`, `gpt-5-mini`, `gpt-5-nano`, `gpt-4.1`, `gpt-4.1-mini`, `gpt-4.1-nano`, `gpt-4o`, `gpt-4o-mini`, `gpt-4-turbo` | | Anthropic | `claude-sonnet-4-6`, `claude-sonnet-4-5`, `claude-sonnet-4`, `claude-haiku-4-5`, `claude-3-7-sonnet`, `claude-3-5-sonnet`, `claude-3-haiku` | | Google | `gemini-3.1-flash-lite-preview`, `gemini-3-pro-preview`, `gemini-3-flash-preview`, `gemini-2.5-flash`, `gemini-2.5-flash-lite`, `gemini-2.0-flash`, `gemini-2.0-flash-lite` | | ElevenLabs | `glm-45-air-fp8`, `qwen3-30b-a3b`, `gpt-oss-120b` | | Custom | `custom-llm` (bring your own endpoint) |

Use `GET /v1/convai/llm/list` to inspect the current model catalog, including deprecation state, token/context limits, and capability flags such as image-input support.

**Popular voices:** `JBFqnCBsd6RMkjVDRZzb` (George), `EXAVITQu4vr4xnSDxMaL` (Sarah), `onwK4e9ZLuTAKqWW03F9` (Daniel), `XB0fDUnXU5powFXDhCwa` (Charlotte)

**Turn eagerness:** `patient` (waits longer for user to finish), `normal`, or `eager` (responds quickly)

See [Agent Configuration](references/agent-configuration.md) for all options.

## Tools

Extend agents with webhook, client, or built-in system tools. Tools are defined inside `conversation_config.agent.prompt`:

Workspace environment variables can resolve per-environment server tool URLs, headers, and auth connections, and runtime system variables such as `{{system__conversation_history}}` can pass full conversation context into tool calls when needed.

```python "prompt": { "prompt": "You are a helpful assistant that can check the weather.", "llm": "gemini-2.0-flash", "tools": [ # Webhook: server-side API call {"type": "webhook", "name": "get_weather", "description": "Get weather", "api_schema": {"url": "https://api.example.com/weather", "method": "POST", "request_body_schema": {"type": "object", "properties": {"location": {"type": "string"}}, "required": ["location"]}}}, # Client: runs in the browser {"type": "client", "name": "show_product", "description": "Display a product", "parameters": {"type": "object", "properties": {"productId": {"type": "string"}}, "required": ["productId"]}} ], "built_in_tools": { "end_call": {}, "transfer_to_number": {"transfers": [{"transfer_destination": {"type": "phone", "phone_number": "+1234567890"}, "condition": "User asks for human support"}]} } } ```

**Client tools** run in browser: ```javascript clientTools: { show_product: async ({ productId }) => { document.getElementById("product").src = `/products/${productId}`; return { success: true }; } } ```

See [Client Tools Reference](references/client-tools.md) for complete documentation.

## Widget Embedding

```html <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`.

See [Widget Embedding Reference](references/widget-embedding.md) for all options.

## Outbound Calls

Make outbound phone calls using your agent via Twilio integration:

### Python

```python response = client.conversational_ai.twilio.outbound_call( agent_id="your-agent-id", agent_phone_number_id="your-phone-number-id", to_number="+1234567890", call_recording_enabled=True ) print(f"Call initiated: {response.conversation_id}") ```

### JavaScript

```javascript const response = await client.conversationalAi.twilio.outboundCall({ agentId: "your-agent-id", agentPhoneNumberId: "your-phone-number-id", toNumber: "+1234567890", callRecordingEnabled: true, }); ```

### cURL

```bash 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", "call_recording_enabled": true}' ```

See [Outbound Calls Reference](references/outbound-calls.md) for configuration overrides and dynamic variables.

## Managing Agents

### Using CLI (Recommended)

```bash # List agents and check status elevenlabs agents list elevenlabs agents status

# Import agents from platform to local config elevenlabs agents pull # Import all agents elevenlabs agents pull --agent <agent-id> # Import specific agent

# Push local changes to platform elevenlabs agents push # Upload configurations elevenlabs agents push --dry-run # Preview changes first

# Add tools elevenlabs tools add-webhook "Weather API" elevenlabs tools add-client "UI Tool" ```

### Project Structure

The CLI creates a project structure for managing agents:

``` your_project/ ├── agents.json # Agent definitions ├── tools.json # Tool configurations ├── tests.json # Test configurations ├── agent_configs/ # Individual agent configs ├── tool_configs/ # Individual tool configs └── test_configs/ # Individual test configs ```

### SDK Examples

```python # List agents = client.conversational_ai.agents.list()

# Get agent = client.conversational_ai.agents.get(agent_id="your-agent-id")

# Update (partial - only include fields to change) client.conversational_ai.agents.update(agent_id="your-agent-id", name="New Name") client.conversational_ai.agents.update(agent_id="your-agent-id", conversation_config={ "agent": {"prompt": {"prompt": "New instructions", "llm": "claude-sonnet-4"}} })

# Delete client.conversational_ai.agents.delete(agent_id="your-agent-id") ```

See [Agent Configuration](references/agent-configuration.md) for all configuration options and SDK examples.

## Error Handling

```python 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

- [Installation Guide](references/installation.md) - SDK setup and migration - [Agent Configuration](references/agent-configuration.md) - All config options and CRUD examples - [Client Tools](references/client-tools.md) - Webhook, client, and system tools - [Widget Embedding](references/widget-embedding.md) - Website integration - [Outbound Calls](references/outbound-calls.md) - Twilio phone call integration

--- 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](references/installation.md) for CLI and SDK setup.

## Quick Start with CLI

The ElevenLabs CLI is the recommended way to create and manage agents:

```bash # Install CLI and authenticate npm install -g @elevenlabs/cli elevenlabs auth login

# Initialize project and create an agent elevenlabs agents init elevenlabs agents add "My Assistant" --template complete

# Push to ElevenLabs platform elevenlabs agents push ```

**Available templates:** `complete`, `minimal`, `voice-only`, `text-only`, `customer-service`, `assistant`

### Python

```python from elevenlabs import ElevenLabs

client = ElevenLabs()

agent = client.conversational_ai.agents.create( name="My Assistant", enable_versioning=True, conversation_config={ "agent": { "first_message": "Hello! How can I help?", "language": "en", "prompt": { "prompt": "You are a helpful assistant. Be concise and friendly.", "llm": "gemini-2.0-flash", "temperature": 0.7 } }, "tts": {"voice_id": "JBFqnCBsd6RMkjVDRZzb"} } ) ```

### JavaScript

```javascript import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js"; const client = new ElevenLabsClient();

const agent = await client.conversationalAi.agents.create({ name: "My Assistant", enableVersioning: true, conversationConfig: { agent: { firstMessage: "Hello! How can I help?", language: "en", prompt: { prompt: "You are a helpful assistant.", llm: "gemini-2.0-flash", temperature: 0.7 } }, tts: { voiceId: "JBFqnCBsd6RMkjVDRZzb" } } }); ```

### cURL

```bash curl -X POST "https://api.elevenlabs.io/v1/convai/agents/create?enable_versioning=true" \ -H "xi-api-key: $ELEVENLABS_API_KEY" -H "Content-Type: application/json" \ -d '{"name": "My Assistant", "conversation_config": {"agent": {"first_message": "Hello!", "language": "en", "prompt": {"prompt": "You are helpful.", "llm": "gemini-2.0-flash"}}, "tts": {"voice_id": "JBFqnCBsd6RMkjVDRZzb"}}}' ```

## Starting Conversations

**Server-side (Python):** Get signed URL for client connection: ```python signed_url = client.conversational_ai.conversations.get_signed_url( agent_id="your-agent-id", environment="staging", ) ```

**Client-side (JavaScript):** ```javascript import { Conversation } from "@elevenlabs/client";

const conversation = await Conversation.startSession({ agentId: "your-agent-id", environment: "staging", onMessage: (msg) => console.log("Agent:", msg.message), onUserTranscript: (t) => console.log("User:", t.message), onError: (e) => console.error(e) }); ```

**React Hook:** ```typescript import { useConversation } from "@elevenlabs/react";

const conversation = useConversation({ onMessage: (msg) => console.log(msg) }); // Get a signed URL for the target environment from your backend, then: await conversation.startSession({ signedUrl: token }); ```

## Configuration

| Provider | Models | |----------|--------| | OpenAI | `gpt-5`, `gpt-5-mini`, `gpt-5-nano`, `gpt-4.1`, `gpt-4.1-mini`, `gpt-4.1-nano`, `gpt-4o`, `gpt-4o-mini`, `gpt-4-turbo` | | Anthropic | `claude-sonnet-4-6`, `claude-sonnet-4-5`, `claude-sonnet-4`, `claude-haiku-4-5`, `claude-3-7-sonnet`, `claude-3-5-sonnet`, `claude-3-haiku` | | Google | `gemini-3.1-flash-lite-preview`, `gemini-3-pro-preview`, `gemini-3-flash-preview`, `gemini-2.5-flash`, `gemini-2.5-flash-lite`, `gemini-2.0-flash`, `gemini-2.0-flash-lite` | | ElevenLabs | `glm-45-air-fp8`, `qwen3-30b-a3b`, `gpt-oss-120b` | | Custom | `custom-llm` (bring your own endpoint) |

Use `GET /v1/convai/llm/list` to inspect the current model catalog, including deprecation state, token/context limits, and capability flags such as image-input support.

**Popular voices:** `JBFqnCBsd6RMkjVDRZzb` (George), `EXAVITQu4vr4xnSDxMaL` (Sarah), `onwK4e9ZLuTAKqWW03F9` (Daniel), `XB0fDUnXU5powFXDhCwa` (Charlotte)

**Turn eagerness:** `patient` (waits longer for user to finish), `normal`, or `eager` (responds quickly)

See [Agent Configuration](references/agent-configuration.md) for all options.

## Tools

Extend agents with webhook, client, or built-in system tools. Tools are defined inside `conversation_config.agent.prompt`:

Workspace environment variables can resolve per-environment server tool URLs, headers, and auth connections, and runtime system variables such as `{{system__conversation_history}}` can pass full conversation context into tool calls when needed.

```python "prompt": { "prompt": "You are a helpful assistant that can check the weather.", "llm": "gemini-2.0-flash", "tools": [ # Webhook: server-side API call {"type": "webhook", "name": "get_weather", "description": "Get weather", "api_schema": {"url": "https://api.example.com/weather", "method": "POST", "request_body_schema": {"type": "object", "properties": {"location": {"type": "string"}}, "required": ["location"]}}}, # Client: runs in the browser {"type": "client", "name": "show_product", "description": "Display a product", "parameters": {"type": "object", "properties": {"productId": {"type": "string"}}, "required": ["productId"]}} ], "built_in_tools": { "end_call": {}, "transfer_to_number": {"transfers": [{"transfer_destination": {"type": "phone", "phone_number": "+1234567890"}, "condition": "User asks for human support"}]} } } ```

**Client tools** run in browser: ```javascript clientTools: { show_product: async ({ productId }) => { document.getElementById("product").src = `/products/${productId}`; return { success: true }; } } ```

See [Client Tools Reference](references/client-tools.md) for complete documentation.

## Widget Embedding

```html <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`.

See [Widget Embedding Reference](references/widget-embedding.md) for all options.

## Outbound Calls

Make outbound phone calls using your agent via Twilio integration:

### Python

```python response = client.conversational_ai.twilio.outbound_call( agent_id="your-agent-id", agent_phone_number_id="your-phone-number-id", to_number="+1234567890", call_recording_enabled=True ) print(f"Call initiated: {response.conversation_id}") ```

### JavaScript

```javascript const response = await client.conversationalAi.twilio.outboundCall({ agentId: "your-agent-id", agentPhoneNumberId: "your-phone-number-id", toNumber: "+1234567890", callRecordingEnabled: true, }); ```

### cURL

```bash 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", "call_recording_enabled": true}' ```

See [Outbound Calls Reference](references/outbound-calls.md) for configuration overrides and dynamic variables.

## Managing Agents

### Using CLI (Recommended)

```bash # List agents and check status elevenlabs agents list elevenlabs agents status

# Import agents from platform to local config elevenlabs agents pull # Import all agents elevenlabs agents pull --agent <agent-id> # Import specific agent

# Push local changes to platform elevenlabs agents push # Upload configurations elevenlabs agents push --dry-run # Preview changes first

# Add tools elevenlabs tools add-webhook "Weather API" elevenlabs tools add-client "UI Tool" ```

### Project Structure

The CLI creates a project structure for managing agents:

``` your_project/ ├── agents.json # Agent definitions ├── tools.json # Tool configurations ├── tests.json # Test configurations ├── agent_configs/ # Individual agent configs ├── tool_configs/ # Individual tool configs └── test_configs/ # Individual test configs ```

### SDK Examples

```python # List agents = client.conversational_ai.agents.list()

# Get agent = client.conversational_ai.agents.get(agent_id="your-agent-id")

# Update (partial - only include fields to change) client.conversational_ai.agents.update(agent_id="your-agent-id", name="New Name") client.conversational_ai.agents.update(agent_id="your-agent-id", conversation_config={ "agent": {"prompt": {"prompt": "New instructions", "llm": "claude-sonnet-4"}} })

# Delete client.conversational_ai.agents.delete(agent_id="your-agent-id") ```

See [Agent Configuration](references/agent-configuration.md) for all configuration options and SDK examples.

## Error Handling

```python 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

- [Installation Guide](references/installation.md) - SDK setup and migration - [Agent Configuration](references/agent-configuration.md) - All config options and CRUD examples - [Client Tools](references/client-tools.md) - Webhook, client, and system tools - [Widget Embedding](references/widget-embedding.md) - Website integration - [Outbound Calls](references/outbound-calls.md) - Twilio phone call integration

--- 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](references/installation.md) for CLI and SDK setup.

## Quick Start with CLI

The ElevenLabs CLI is the recommended way to create and manage agents:

```bash # Install CLI and authenticate npm install -g @elevenlabs/cli elevenlabs auth login

# Initialize project and create an agent elevenlabs agents init elevenlabs agents add "My Assistant" --template complete

# Push to ElevenLabs platform elevenlabs agents push ```

**Available templates:** `complete`, `minimal`, `voice-only`, `text-only`, `customer-service`, `assistant`

### Python

```python from elevenlabs import ElevenLabs

client = ElevenLabs()

agent = client.conversational_ai.agents.create( name="My Assistant", enable_versioning=True, conversation_config={ "agent": { "first_message": "Hello! How can I help?", "language": "en", "prompt": { "prompt": "You are a helpful assistant. Be concise and friendly.", "llm": "gemini-2.0-flash", "temperature": 0.7 } }, "tts": {"voice_id": "JBFqnCBsd6RMkjVDRZzb"} } ) ```

### JavaScript

```javascript import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js"; const client = new ElevenLabsClient();

const agent = await client.conversationalAi.agents.create({ name: "My Assistant", enableVersioning: true, conversationConfig: { agent: { firstMessage: "Hello! How can I help?", language: "en", prompt: { prompt: "You are a helpful assistant.", llm: "gemini-2.0-flash", temperature: 0.7 } }, tts: { voiceId: "JBFqnCBsd6RMkjVDRZzb" } } }); ```

### cURL

```bash curl -X POST "https://api.elevenlabs.io/v1/convai/agents/create?enable_versioning=true" \ -H "xi-api-key: $ELEVENLABS_API_KEY" -H "Content-Type: application/json" \ -d '{"name": "My Assistant", "conversation_config": {"agent": {"first_message": "Hello!", "language": "en", "prompt": {"prompt": "You are helpful.", "llm": "gemini-2.0-flash"}}, "tts": {"voice_id": "JBFqnCBsd6RMkjVDRZzb"}}}' ```

## Starting Conversations

**Server-side (Python):** Get signed URL for client connection: ```python signed_url = client.conversational_ai.conversations.get_signed_url( agent_id="your-agent-id", environment="staging", ) ```

**Client-side (JavaScript):** ```javascript import { Conversation } from "@elevenlabs/client";

const conversation = await Conversation.startSession({ agentId: "your-agent-id", environment: "staging", onMessage: (msg) => console.log("Agent:", msg.message), onUserTranscript: (t) => console.log("User:", t.message), onError: (e) => console.error(e) }); ```

**React Hook:** ```typescript import { useConversation } from "@elevenlabs/react";

const conversation = useConversation({ onMessage: (msg) => console.log(msg) }); // Get a signed URL for the target environment from your backend, then: await conversation.startSession({ signedUrl: token }); ```

## Configuration

| Provider | Models | |----------|--------| | OpenAI | `gpt-5`, `gpt-5-mini`, `gpt-5-nano`, `gpt-4.1`, `gpt-4.1-mini`, `gpt-4.1-nano`, `gpt-4o`, `gpt-4o-mini`, `gpt-4-turbo` | | Anthropic | `claude-sonnet-4-6`, `claude-sonnet-4-5`, `claude-sonnet-4`, `claude-haiku-4-5`, `claude-3-7-sonnet`, `claude-3-5-sonnet`, `claude-3-haiku` | | Google | `gemini-3.1-flash-lite-preview`, `gemini-3-pro-preview`, `gemini-3-flash-preview`, `gemini-2.5-flash`, `gemini-2.5-flash-lite`, `gemini-2.0-flash`, `gemini-2.0-flash-lite` | | ElevenLabs | `glm-45-air-fp8`, `qwen3-30b-a3b`, `gpt-oss-120b` | | Custom | `custom-llm` (bring your own endpoint) |

Use `GET /v1/convai/llm/list` to inspect the current model catalog, including deprecation state, token/context limits, and capability flags such as image-input support.

**Popular voices:** `JBFqnCBsd6RMkjVDRZzb` (George), `EXAVITQu4vr4xnSDxMaL` (Sarah), `onwK4e9ZLuTAKqWW03F9` (Daniel), `XB0fDUnXU5powFXDhCwa` (Charlotte)

**Turn eagerness:** `patient` (waits longer for user to finish), `normal`, or `eager` (responds quickly)

See [Agent Configuration](references/agent-configuration.md) for all options.

## Tools

Extend agents with webhook, client, or built-in system tools. Tools are defined inside `conversation_config.agent.prompt`:

Workspace environment variables can resolve per-environment server tool URLs, headers, and auth connections, and runtime system variables such as `{{system__conversation_history}}` can pass full conversation context into tool calls when needed.

```python "prompt": { "prompt": "You are a helpful assistant that can check the weather.", "llm": "gemini-2.0-flash", "tools": [ # Webhook: server-side API call {"type": "webhook", "name": "get_weather", "description": "Get weather", "api_schema": {"url": "https://api.example.com/weather", "method": "POST", "request_body_schema": {"type": "object", "properties": {"location": {"type": "string"}}, "required": ["location"]}}}, # Client: runs in the browser {"type": "client", "name": "show_product", "description": "Display a product", "parameters": {"type": "object", "properties": {"productId": {"type": "string"}}, "required": ["productId"]}} ], "built_in_tools": { "end_call": {}, "transfer_to_number": {"transfers": [{"transfer_destination": {"type": "phone", "phone_number": "+1234567890"}, "condition": "User asks for human support"}]} } } ```

**Client tools** run in browser: ```javascript clientTools: { show_product: async ({ productId }) => { document.getElementById("product").src = `/products/${productId}`; return { success: true }; } } ```

See [Client Tools Reference](references/client-tools.md) for complete documentation.

## Widget Embedding

```html <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`.

See [Widget Embedding Reference](references/widget-embedding.md) for all options.

## Outbound Calls

Make outbound phone calls using your agent via Twilio integration:

### Python

```python response = client.conversational_ai.twilio.outbound_call( agent_id="your-agent-id", agent_phone_number_id="your-phone-number-id", to_number="+1234567890", call_recording_enabled=True ) print(f"Call initiated: {response.conversation_id}") ```

### JavaScript

```javascript const response = await client.conversationalAi.twilio.outboundCall({ agentId: "your-agent-id", agentPhoneNumberId: "your-phone-number-id", toNumber: "+1234567890", callRecordingEnabled: true, }); ```

### cURL

```bash 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", "call_recording_enabled": true}' ```

See [Outbound Calls Reference](references/outbound-calls.md) for configuration overrides and dynamic variables.

## Managing Agents

### Using CLI (Recommended)

```bash # List agents and check status elevenlabs agents list elevenlabs agents status

# Import agents from platform to local config elevenlabs agents pull # Import all agents elevenlabs agents pull --agent <agent-id> # Import specific agent

# Push local changes to platform elevenlabs agents push # Upload configurations elevenlabs agents push --dry-run # Preview changes first

# Add tools elevenlabs tools add-webhook "Weather API" elevenlabs tools add-client "UI Tool" ```

### Project Structure

The CLI creates a project structure for managing agents:

``` your_project/ ├── agents.json # Agent definitions ├── tools.json # Tool configurations ├── tests.json # Test configurations ├── agent_configs/ # Individual agent configs ├── tool_configs/ # Individual tool configs └── test_configs/ # Individual test configs ```

### SDK Examples

```python # List agents = client.conversational_ai.agents.list()

# Get agent = client.conversational_ai.agents.get(agent_id="your-agent-id")

# Update (partial - only include fields to change) client.conversational_ai.agents.update(agent_id="your-agent-id", name="New Name") client.conversational_ai.agents.update(agent_id="your-agent-id", conversation_config={ "agent": {"prompt": {"prompt": "New instructions", "llm": "claude-sonnet-4"}} })

# Delete client.conversational_ai.agents.delete(agent_id="your-agent-id") ```

See [Agent Configuration](references/agent-configuration.md) for all configuration options and SDK examples.

## Error Handling

```python 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

- [Installation Guide](references/installation.md) - SDK setup and migration - [Agent Configuration](references/agent-configuration.md) - All config options and CRUD examples - [Client Tools](references/client-tools.md) - Webhook, client, and system tools - [Widget Embedding](references/widget-embedding.md) - Website integration - [Outbound Calls](references/outbound-calls.md) - Twilio phone call integration

--- 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](references/installation.md) for CLI and SDK setup.

## Quick Start with CLI

The ElevenLabs CLI is the recommended way to create and manage agents:

```bash # Install CLI and authenticate npm install -g @elevenlabs/cli elevenlabs auth login

# Initialize project and create an agent elevenlabs agents init elevenlabs agents add "My Assistant" --template complete

# Push to ElevenLabs platform elevenlabs agents push ```

**Available templates:** `complete`, `minimal`, `voice-only`, `text-only`, `customer-service`, `assistant`

### Python

```python from elevenlabs import ElevenLabs

client = ElevenLabs()

agent = client.conversational_ai.agents.create( name="My Assistant", enable_versioning=True, conversation_config={ "agent": { "first_message": "Hello! How can I help?", "language": "en", "prompt": { "prompt": "You are a helpful assistant. Be concise and friendly.", "llm": "gemini-2.0-flash", "temperature": 0.7 } }, "tts": {"voice_id": "JBFqnCBsd6RMkjVDRZzb"} } ) ```

### JavaScript

```javascript import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js"; const client = new ElevenLabsClient();

const agent = await client.conversationalAi.agents.create({ name: "My Assistant", enableVersioning: true, conversationConfig: { agent: { firstMessage: "Hello! How can I help?", language: "en", prompt: { prompt: "You are a helpful assistant.", llm: "gemini-2.0-flash", temperature: 0.7 } }, tts: { voiceId: "JBFqnCBsd6RMkjVDRZzb" } } }); ```

### cURL

```bash curl -X POST "https://api.elevenlabs.io/v1/convai/agents/create?enable_versioning=true" \ -H "xi-api-key: $ELEVENLABS_API_KEY" -H "Content-Type: application/json" \ -d '{"name": "My Assistant", "conversation_config": {"agent": {"first_message": "Hello!", "language": "en", "prompt": {"prompt": "You are helpful.", "llm": "gemini-2.0-flash"}}, "tts": {"voice_id": "JBFqnCBsd6RMkjVDRZzb"}}}' ```

## Starting Conversations

**Server-side (Python):** Get signed URL for client connection: ```python signed_url = client.conversational_ai.conversations.get_signed_url( agent_id="your-agent-id", environment="staging", ) ```

**Client-side (JavaScript):** ```javascript import { Conversation } from "@elevenlabs/client";

const conversation = await Conversation.startSession({ agentId: "your-agent-id", environment: "staging", onMessage: (msg) => console.log("Agent:", msg.message), onUserTranscript: (t) => console.log("User:", t.message), onError: (e) => console.error(e) }); ```

**React Hook:** ```typescript import { useConversation } from "@elevenlabs/react";

const conversation = useConversation({ onMessage: (msg) => console.log(msg) }); // Get a signed URL for the target environment from your backend, then: await conversation.startSession({ signedUrl: token }); ```

## Configuration

| Provider | Models | |----------|--------| | OpenAI | `gpt-5`, `gpt-5-mini`, `gpt-5-nano`, `gpt-4.1`, `gpt-4.1-mini`, `gpt-4.1-nano`, `gpt-4o`, `gpt-4o-mini`, `gpt-4-turbo` | | Anthropic | `claude-sonnet-4-6`, `claude-sonnet-4-5`, `claude-sonnet-4`, `claude-haiku-4-5`, `claude-3-7-sonnet`, `claude-3-5-sonnet`, `claude-3-haiku` | | Google | `gemini-3.1-flash-lite-preview`, `gemini-3-pro-preview`, `gemini-3-flash-preview`, `gemini-2.5-flash`, `gemini-2.5-flash-lite`, `gemini-2.0-flash`, `gemini-2.0-flash-lite` | | ElevenLabs | `glm-45-air-fp8`, `qwen3-30b-a3b`, `gpt-oss-120b` | | Custom | `custom-llm` (bring your own endpoint) |

Use `GET /v1/convai/llm/list` to inspect the current model catalog, including deprecation state, token/context limits, and capability flags such as image-input support.

**Popular voices:** `JBFqnCBsd6RMkjVDRZzb` (George), `EXAVITQu4vr4xnSDxMaL` (Sarah), `onwK4e9ZLuTAKqWW03F9` (Daniel), `XB0fDUnXU5powFXDhCwa` (Charlotte)

**Turn eagerness:** `patient` (waits longer for user to finish), `normal`, or `eager` (responds quickly)

See [Agent Configuration](references/agent-configuration.md) for all options.

## Tools

Extend agents with webhook, client, or built-in system tools. Tools are defined inside `conversation_config.agent.prompt`:

Workspace environment variables can resolve per-environment server tool URLs, headers, and auth connections, and runtime system variables such as `{{system__conversation_history}}` can pass full conversation context into tool calls when needed.

```python "prompt": { "prompt": "You are a helpful assistant that can check the weather.", "llm": "gemini-2.0-flash", "tools": [ # Webhook: server-side API call {"type": "webhook", "name": "get_weather", "description": "Get weather", "api_schema": {"url": "https://api.example.com/weather", "method": "POST", "request_body_schema": {"type": "object", "properties": {"location": {"type": "string"}}, "required": ["location"]}}}, # Client: runs in the browser {"type": "client", "name": "show_product", "description": "Display a product", "parameters": {"type": "object", "properties": {"productId": {"type": "string"}}, "required": ["productId"]}} ], "built_in_tools": { "end_call": {}, "transfer_to_number": {"transfers": [{"transfer_destination": {"type": "phone", "phone_number": "+1234567890"}, "condition": "User asks for human support"}]} } } ```

**Client tools** run in browser: ```javascript clientTools: { show_product: async ({ productId }) => { document.getElementById("product").src = `/products/${productId}`; return { success: true }; } } ```

See [Client Tools Reference](references/client-tools.md) for complete documentation.

## Widget Embedding

```html <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`.

See [Widget Embedding Reference](references/widget-embedding.md) for all options.

## Outbound Calls

Make outbound phone calls using your agent via Twilio integration:

### Python

```python response = client.conversational_ai.twilio.outbound_call( agent_id="your-agent-id", agent_phone_number_id="your-phone-number-id", to_number="+1234567890", call_recording_enabled=True ) print(f"Call initiated: {response.conversation_id}") ```

### JavaScript

```javascript const response = await client.conversationalAi.twilio.outboundCall({ agentId: "your-agent-id", agentPhoneNumberId: "your-phone-number-id", toNumber: "+1234567890", callRecordingEnabled: true, }); ```

### cURL

```bash 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", "call_recording_enabled": true}' ```

See [Outbound Calls Reference](references/outbound-calls.md) for configuration overrides and dynamic variables.

## Managing Agents

### Using CLI (Recommended)

```bash # List agents and check status elevenlabs agents list elevenlabs agents status

# Import agents from platform to local config elevenlabs agents pull # Import all agents elevenlabs agents pull --agent <agent-id> # Import specific agent

# Push local changes to platform elevenlabs agents push # Upload configurations elevenlabs agents push --dry-run # Preview changes first

# Add tools elevenlabs tools add-webhook "Weather API" elevenlabs tools add-client "UI Tool" ```

### Project Structure

The CLI creates a project structure for managing agents:

``` your_project/ ├── agents.json # Agent definitions ├── tools.json # Tool configurations ├── tests.json # Test configurations ├── agent_configs/ # Individual agent configs ├── tool_configs/ # Individual tool configs └── test_configs/ # Individual test configs ```

### SDK Examples

```python # List agents = client.conversational_ai.agents.list()

# Get agent = client.conversational_ai.agents.get(agent_id="your-agent-id")

# Update (partial - only include fields to change) client.conversational_ai.agents.update(agent_id="your-agent-id", name="New Name") client.conversational_ai.agents.update(agent_id="your-agent-id", conversation_config={ "agent": {"prompt": {"prompt": "New instructions", "llm": "claude-sonnet-4"}} })

# Delete client.conversational_ai.agents.delete(agent_id="your-agent-id") ```

See [Agent Configuration](references/agent-configuration.md) for all configuration options and SDK examples.

## Error Handling

```python 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

- [Installation Guide](references/installation.md) - SDK setup and migration - [Agent Configuration](references/agent-configuration.md) - All config options and CRUD examples - [Client Tools](references/client-tools.md) - Webhook, client, and system tools - [Widget Embedding](references/widget-embedding.md) - Website integration - [Outbound Calls](references/outbound-calls.md) - Twilio phone call integration