Implementation:Elevenlabs Elevenlabs python GetAgentResponseModel

Field	Value
source	Elevenlabs_Elevenlabs_python
domains	Conversational AI, Agent Management, API Response
last_updated	2026-02-15

Overview

Description

GetAgentResponseModel is a Pydantic model representing the full response returned when retrieving an agent from the ElevenLabs Conversational AI API. It is the top-level response object that aggregates all facets of an agent's configuration, including conversation settings, metadata, platform settings, phone numbers, WhatsApp accounts, workflows, and version/branch tracking.

This model is auto-generated by Fern from the ElevenLabs API definition and inherits from UncheckedBaseModel. It serves as the primary data structure for agent retrieval operations.

Usage

GetAgentResponseModel is returned by the ElevenLabs API when fetching an agent by ID. It provides a comprehensive view of the agent's current state, including all configuration, metadata, and connected channels (phone, WhatsApp). It is typically consumed by client applications to display or manage agent settings.

Code Reference

Source Location

src/elevenlabs/types/get_agent_response_model.py

Class Signature

class GetAgentResponseModel(UncheckedBaseModel):
    ...

Import Statement

from elevenlabs.types import GetAgentResponseModel

I/O Contract

Field	Type	Required	Description
`agent_id`	`str`	Yes	The ID of the agent.
`name`	`str`	Yes	The name of the agent.
`conversation_config`	`ConversationalConfig`	Yes	The conversation configuration of the agent.
`metadata`	`AgentMetadataResponseModel`	Yes	The metadata of the agent.
`platform_settings`	`Optional[AgentPlatformSettingsResponseModel]`	No	The platform settings of the agent.
`phone_numbers`	`Optional[List[GetAgentResponseModelPhoneNumbersItem]]`	No	The phone numbers of the agent.
`whatsapp_accounts`	`Optional[List[GetWhatsAppAccountResponse]]`	No	WhatsApp accounts assigned to the agent.
`workflow`	`Optional[AgentWorkflowResponseModel]`	No	The workflow of the agent.
`access_info`	`Optional[ResourceAccessInfo]`	No	The access information of the agent for the user.
`tags`	`Optional[List[str]]`	No	Agent tags used to categorize the agent.
`version_id`	`Optional[str]`	No	The ID of the version the agent is on.
`branch_id`	`Optional[str]`	No	The ID of the branch the agent is on.
`main_branch_id`	`Optional[str]`	No	The ID of the main branch for this agent.

Usage Examples

Retrieving and Inspecting an Agent

from elevenlabs import ElevenLabs

client = ElevenLabs(api_key="your-api-key")
agent = client.conversational_ai.agents.get(agent_id="agent_abc123")

# agent is a GetAgentResponseModel instance
print(f"Agent: {agent.name} (ID: {agent.agent_id})")
print(f"Branch: {agent.branch_id}")
print(f"Tags: {agent.tags}")

Accessing Nested Configuration

# Access the conversation configuration
conv_config = agent.conversation_config

# Access phone numbers if assigned
if agent.phone_numbers:
    for phone in agent.phone_numbers:
        print(f"Phone: {phone}")

# Check version and branch info
if agent.version_id:
    print(f"Version: {agent.version_id}")
if agent.branch_id:
    print(f"Branch: {agent.branch_id}")

Related Pages

Elevenlabs_Elevenlabs_python_AgentConfig - Core agent configuration nested within the conversation config
Elevenlabs_Elevenlabs_python_AgentBranchSummary - Branch summary model for agent versioning
Elevenlabs_Elevenlabs_python_PromptAgentApiModelInput - Agent prompt configuration input
Elevenlabs_Elevenlabs_python_AuthSettings - Authentication settings for the agent

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Principle

Implementation

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