agents

What this skill does

# 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",
    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",
  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" \
  -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

### Temporary LiveKit WebSocket Pin

Until the ElevenLabs LiveKit server supports `/rtc/v1`, browser clients using WebRTC can fail or stall during the underlying LiveKit WebSocket handshake with `livekit-client` versions newer than `2.16.1`. For React, Next.js, Electron, or other `@elevenlabs/client` / `@elevenlabs/react` integrations that use `connectionType: "webrtc"` or hit `wss://livekit.rtc.elevenlabs.io/rtc/v1`, add this temporary pin to `package.json`:

```json
{
  "overrides": {
    "livekit-client": "2.16.1"
  }
}
```

Use the pin when the app logs `/rtc/v1` 404s, `v1 RTC path not found`, or `could not establish pc connection` during session startup. This is a LiveKit server compatibility workaround for WebRTC sessions, not the ElevenLabs `connectionType: "websocket"` transport. Remove it after the upstream LiveKit server or SDK issue is fixed.

**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:** Wrap hook consumers in `ConversationProvider`. Prefer granular hooks such as
`useConversationControls` and `useConversationStatus` for session controls and UI state;
`useConversation` remains available as the convenience all-in-one hook. Pass provider-level
callbacks such as `onError` when you want React to handle conversation errors in one place.
```typescript
import {
  ConversationProvider,
  useConversationControls,
  useConversationStatus,
} from "@elevenlabs/react";

function Agent({ signedUrl }: { signedUrl: string }) {
  const { startSession, endSession } = useConversationControls();
  const { status } = useConversationStatus();

  if (status === "connected") {
    return <button onClick={endSession}>End conversation</button>;
  }

  return (
    <button onClick={() => startSession({ signedUrl })}>
      Start conversation
    </button>
  );
}

function App({ signedUrl }: { signedUrl: string }) {
  return (
    <ConversationProvider
      onError={(error) => console.error("Conversation error:", error)}
    >
      <Agent signedUrl={signedUrl} />
    </ConversationProvider>
  );
}
```

## Configuration

| Provider | Models |
|----------|--------|
| OpenAI | `gpt-5.5`, `gpt-5.5-2026-04-23`, `gpt-5.4`, `gpt-5.4-mini`, `gpt-5.4-nano`, `gpt-5.4-2026-03-05`, `gpt-5.4-mini-2026-03-17`, `gpt-5.4-nano-2026-03-17`, `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-opus-4-7`, `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-3.1-pro-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`, `qwen36-35b-a3b`, `qwen35-35b-a3b`, `qwen35-397b-a17b`, `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, capability flags such as image-input support, and model-specific reasoning effort 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.

## System Prompt Structure

Section the prompt with markdown headings — the model prioritizes and interprets instructions more reliably ([prompting guide](https://elevenlabs.io/docs/eleven-agents/best-practices/prompting-guide)):

```
# Personality   – named character, 2-3 traits
# Environment   – where they work, who they talk to
# Tone          – vocal style as 4-5 bullets
# Goal          – what success looks like (numbered for multi-step flows)
```

Keep instructions short and action-based. Mark critical steps with "This step is important." For critical refusal/safety rules, include concise instructions in the prompt and also configure independent custom Guardrails via `platform_settings.guardrails` (see [Guardrails](#guardrails)).

## 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"